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      Spotlight on islands: on the origin and diversification of an ancient lineage of the Italian wall lizard Podarcis siculus in the western Pontine Islands

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          Abstract

          Groups of proximate continental islands may conceal more tangled phylogeographic patterns than oceanic archipelagos as a consequence of repeated sea level changes, which allow populations to experience gene flow during periods of low sea level stands and isolation by vicariant mechanisms during periods of high sea level stands. Here, we describe for the first time an ancient and diverging lineage of the Italian wall lizard Podarcis siculus from the western Pontine Islands. We used nuclear and mitochondrial DNA sequences of 156 individuals with the aim of unraveling their phylogenetic position, while microsatellite loci were used to test several a priori insular biogeographic models of migration with empirical data. Our results suggest that the western Pontine populations colonized the islands early during their Pliocene volcanic formation, while populations from the eastern Pontine Islands seem to have been introduced recently. The inter-island genetic makeup indicates an important role of historical migration, probably due to glacial land bridges connecting islands followed by a recent vicariant mechanism of isolation. Moreover, the most supported migration model predicted higher gene flow among islands which are geographically arranged in parallel. Considering the threatened status of small insular endemic populations, we suggest this new evolutionarily independent unit be given priority in conservation efforts.

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          Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques.

          A very simple, fast, universally applicable and reproducible method to extract high quality megabase genomic DNA from different organisms is described. We applied the same method to extract high quality complex genomic DNA from different tissues (wheat, barley, potato, beans, pear and almond leaves as well as fungi, insects and shrimps' fresh tissue) without any modification. The method does not require expensive and environmentally hazardous reagents and equipment. It can be performed even in low technology laboratories. The amount of tissue required by this method is approximately 50-100 mg. The quantity and the quality of the DNA extracted by this method is high enough to perform hundreds of PCR-based reactions and also to be used in other DNA manipulation techniques such as restriction digestion, Southern blot and cloning.
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            Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach.

            A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source-sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.
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              ORIGINAL ARTICLE: A general dynamic theory of oceanic island biogeography

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                Author and article information

                Contributors
                gabriele.senczuk@uniroma1.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 October 2018
                11 October 2018
                2018
                : 8
                : 15111
                Affiliations
                [1 ]GRID grid.7841.a, Department of Biology and Biotechnology “Charles Darwin”, , University of Rome La Sapienza, ; via borelli 51, Roma, Rome, Italy
                [2 ]ISNI 0000 0004 1757 2304, GRID grid.8404.8, Museum of Zoology and Natural History ‘La Specola’, , University of Florence, ; via Romana 17, Florence, Italy
                [3 ]ISNI 0000 0001 0942 1117, GRID grid.11348.3f, Unit of Evolutionary Biology/Systematic Zoology, Institute of Biochemistry and Biology, , University of Potsdam, ; Karl-Liebknecht-Strasse 24–25, Haus 26, 14476 Potsdam, Germany
                Article
                33326
                10.1038/s41598-018-33326-w
                6181948
                30310095
                efe37b9e-d119-4c8c-a83c-8ad1aca9452d
                © The Author(s) 2018

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

                History
                : 17 April 2018
                : 26 September 2018
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003407, Ministero dell'Istruzione, dell'Università e della Ricerca (Ministry of Education, University and Research);
                Award ID: 00017879/PNM
                Award ID: 00017879/PNM
                Award Recipient :
                Funded by: Università di Roma LA SAPIENZA
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