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      Deep and concordant subdivisions in the self-fertilizing mangrove killifishes (Kryptolebias) revealed by nuclear and mtDNA markers

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          microsatellite analyser(MSA): a platform independent analysis tool for large microsatellite data sets

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            Reliable selfing rate estimates from imperfect population genetic data.

            Genotypic frequencies at codominant marker loci in population samples convey information on mating systems. A classical way to extract this information is to measure heterozygote deficiencies (FIS) and obtain the selfing rate s from FIS = s/(2 - s), assuming inbreeding equilibrium. A major drawback is that heterozygote deficiencies are often present without selfing, owing largely to technical artefacts such as null alleles or partial dominance. We show here that, in the absence of gametic disequilibrium, the multilocus structure can be used to derive estimates of s independent of FIS and free of technical biases. Their statistical power and precision are comparable to those of FIS, although they are sensitive to certain types of gametic disequilibria, a bias shared with progeny-array methods but not FIS. We analyse four real data sets spanning a range of mating systems. In two examples, we obtain s = 0 despite positive FIS, strongly suggesting that the latter are artefactual. In the remaining examples, all estimates are consistent. All the computations have been implemented in a open-access and user-friendly software called rmes (robust multilocus estimate of selfing) available at http://ftp.cefe.cnrs.fr, and can be used on any multilocus data. Being able to extract the reliable information from imperfect data, our method opens the way to make use of the ever-growing number of published population genetic studies, in addition to the more demanding progeny-array approaches, to investigate selfing rates.
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              Comparative phylogeography in a genus of coral reef fishes: biogeographic and genetic concordance in the Caribbean.

              Geographic barriers that limit the movement of individuals between populations may create or maintain phylogenetically discrete lineages. Such barriers are often inferred from geographic surveys of a single mitochondrial marker to identify phylogenetic splits. Mitochondrial DNA, however, has an effective population size one-fourth that of nuclear DNA, which can facilitate the rapid evolution of monophyletic mtDNA lineages in the absence of geographic barriers. The identification of geographic barriers will thus be more robust if barriers are proposed a priori, and tested with multiple independent genetic markers in multiple species. Here, we tested two proposed marine biogeographic breaks located at the Mona Passage in the Caribbean Sea and at the southern end of Exuma Sound in the Bahamas. We sequenced mitochondrial cytochrome b (400 bp) and nuclear rag1 (573 bp) for nine species and colour forms (183 individuals total) within the teleost genus Elacatinus (Gobiidae) that span the proposed breaks. Our results showed that Mona Passage separated mtcyb and rag1 lineages, with no genetic exchange between populations separated by just 23 km. However, the Central Bahamas barrier was only weakly supported by our data. Importantly, neither barrier coincided with deep genetic splits. This suggests that these two barriers did not initially isolate regional populations, but instead disrupt ongoing gene flow between regions. Our inferred relationships further suggested a division of the Caribbean region into northwestern and southeastern regions, a pattern reflected by some freshwater and terrestrial vertebrates. Our results, coupled with genetic and demographic data from other reef fishes and corals, provide robust support for the Mona Passage as a long-term biogeographic barrier for Caribbean animals.
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                Author and article information

                Journal
                Biological Journal of the Linnean Society
                Oxford University Press (OUP)
                0024-4066
                1095-8312
                November 25 2017
                November 25 2017
                : 122
                : 3
                : 558-578
                Article
                10.1093/biolinnean/blx103
                19d44ece-eac4-407b-b0f0-eca27b6b84a4
                © 2017
                History

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