Browsing by Author "Kumagai, Seiji"

Now showing 1 - 7 of 7
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    A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation.
    (Genetics, 2015-11) Redelings, Benjamin D; Kumagai, Seiji; Tatarenkov, Andrey; Wang, Liuyang; Sakai, Ann K; Weller, Stephen G; Culley, Theresa M; Avise, John C; Uyenoyama, Marcy K
    We present a Bayesian method for characterizing the mating system of populations reproducing through a mixture of self-fertilization and random outcrossing. Our method uses patterns of genetic variation across the genome as a basis for inference about reproduction under pure hermaphroditism, gynodioecy, and a model developed to describe the self-fertilizing killifish Kryptolebias marmoratus. We extend the standard coalescence model to accommodate these mating systems, accounting explicitly for multilocus identity disequilibrium, inbreeding depression, and variation in fertility among mating types. We incorporate the Ewens sampling formula (ESF) under the infinite-alleles model of mutation to obtain a novel expression for the likelihood of mating system parameters. Our Markov chain Monte Carlo (MCMC) algorithm assigns locus-specific mutation rates, drawn from a common mutation rate distribution that is itself estimated from the data using a Dirichlet process prior model. Our sampler is designed to accommodate additional information, including observations pertaining to the sex ratio, the intensity of inbreeding depression, and other aspects of reproduction. It can provide joint posterior distributions for the population-wide proportion of uniparental individuals, locus-specific mutation rates, and the number of generations since the most recent outcrossing event for each sampled individual. Further, estimation of all basic parameters of a given model permits estimation of functions of those parameters, including the proportion of the gene pool contributed by each sex and relative effective numbers.
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    Allele frequency spectra in structured populations: Novel-allele probabilities under the labelled coalescent.
    (Theoretical population biology, 2020-06) Uyenoyama, Marcy K; Takebayashi, Naoki; Kumagai, Seiji
    We address the effect of population structure on key properties of the Ewens sampling formula. We use our previously-introduced inductive method for determining exact allele frequency spectrum (AFS) probabilities under the infinite-allele model of mutation and population structure for samples of arbitrary size. Fundamental to the sampling distribution is the novel-allele probability, the probability that given the pattern of variation in the present sample, the next gene sampled belongs to an as-yet-unobserved allelic class. Unlike the case for panmictic populations, the novel-allele probability depends on the AFS of the present sample. We derive a recursion that directly provides the marginal novel-allele probability across AFSs, obviating the need first to determine the probability of each AFS. Our explorations suggest that the marginal novel-allele probability tends to be greater for initial samples comprising fewer alleles and for sampling configurations in which the next-observed gene derives from a deme different from that of the majority of the present sample. Comparison to the efficient importance sampling proposals developed by De Iorio and Griffiths and colleagues indicates that their approximation for the novel-allele probability generally agrees with the true marginal, although it may tend to overestimate the marginal in cases in which the novel-allele probability is high and migration rates are low.
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    Bayesian co-estimation of selfing rate and locus-specific mutation rates for a partially selfing population
    (2017-07-02) Redelings, Benjamin D; Kumagai, Seiji; Wang, Liuyang; Tatarenkov, Andrey; Sakai, Ann K; Weller, Stephen G; Culley, Theresa M; Avise, John C; Uyenoyama, Marcy K
    We present a Bayesian method for characterizing the mating system of populations reproducing through a mixture of self-fertilization and random outcrossing. Our method uses patterns of genetic variation across the genome as a basis for inference about pure hermaphroditism, androdioecy, and gynodioecy. We extend the standard coalescence model to accommodate these mating systems, accounting explicitly for multilocus identity disequilibrium, inbreeding depression, and variation in fertility among mating types. We incorporate the Ewens Sampling Formula (ESF) under the infinite-alleles model of mutation to obtain a novel expression for the likelihood of mating system parameters. Our Markov chain Monte Carlo (MCMC) algorithm assigns locus-specific mutation rates, drawn from a common mutation rate distribution that is itself estimated from the data using a Dirichlet Process Prior (DPP) model. Among the parameters jointly inferred are the population-wide rate of self-fertilization, locus-specific mutation rates, and the number of generations since the most recent outcrossing event for each sampled individual.
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    Genealogical histories in structured populations.
    (Theoretical population biology, 2015-06) Kumagai, Seiji; Uyenoyama, Marcy K
    In genealogies of genes sampled from structured populations, lineages coalesce at rates dependent on the states of the lineages. For migration and coalescence events occurring on comparable time scales, for example, only lineages residing in the same deme of a geographically subdivided population can have descended from a common ancestor in the immediately preceding generation. Here, we explore aspects of genealogical structure in a population comprising two demes, between which migration may occur. We use generating functions to obtain exact densities and moments of coalescence time, number of mutations, total tree length, and age of the most recent common ancestor of the sample. We describe qualitative features of the distribution of gene genealogies, including factors that influence the geographical location of the most recent common ancestor and departures of the distribution of internode lengths from exponential.
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    Inductive determination of allele frequency spectrum probabilities in structured populations.
    (Theoretical population biology, 2019-10) Uyenoyama, Marcy K; Takebayashi, Naoki; Kumagai, Seiji
    We present a method for inductively determining exact allele frequency spectrum (AFS) probabilities for samples derived from a population comprising two demes under the infinite-allele model of mutation. This method builds on a labeled coalescent argument to extend the Ewens sampling formula (ESF) to structured populations. A key departure from the panmictic case is that the AFS conditioned on the number of alleles in the sample is no longer independent of the scaled mutation rate (θ). In particular, biallelic site frequency spectra, widely-used in explorations of genome-wide patterns of variation, depend on the mutation rate in structured populations. Variation in the rate of substitution across loci and through time may contribute to apparent distortions of site frequency spectra exhibited by samples derived from structured populations.
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    The Effect of Competition Among Resources on Phenotypic Evolution of Consumers
    (2010) Kumagai, Seiji

    The pattern of competition among consumers

    is one of the important factors that

    determine if a population of the consumers

    diverges or remains monomophic.

    Despite its importance,

    what factors can affect the pattern

    has not been investigated.

    One of such factors is

    the shape of resource distribution.

    Here I investigate the effect of

    competition among resources.

    Because the competition among resources

    alter the resource distribution,

    the evolutionary dynamics of the consumers

    is also affected.