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      Speciation in Fungal and Oomycete Plant Pathogens

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      Annual Review of Phytopathology
      Annual Reviews

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          Phylogenetic species recognition and species concepts in fungi.

          The operational species concept, i.e., the one used to recognize species, is contrasted to the theoretical species concept. A phylogenetic approach to recognize fungal species based on concordance of multiple gene genealogies is compared to those based on morphology and reproductive behavior. Examples where Phylogenetic Species Recognition has been applied to fungi are reviewed and concerns regarding Phylogenetic Species Recognition are discussed.
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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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              Statistical methods for detecting molecular adaptation.

              The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.
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                Author and article information

                Journal
                Annual Review of Phytopathology
                Annu. Rev. Phytopathol.
                Annual Reviews
                0066-4286
                1545-2107
                August 04 2014
                August 04 2014
                : 52
                : 1
                : 289-316
                Article
                10.1146/annurev-phyto-102313-050056
                24906125
                582d7fb9-18d3-4579-b39d-22312b419c25
                © 2014
                History

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