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A R Rogers

Publications and source records attributed to A R Rogers.

14 recordsLinked to original sources

Population growth makes waves in the distribution of pairwise genetic differences.

Episodes of population growth and decline leave characteristic signatures in the distribution of nucleotide (or restriction) site differences between pairs of individuals. These signatures appear in histograms showing the relative frequencies of pairs of individuals who differ by i sites, where i = 0, 1, .... In this distribution an episode of growth generates a wave that travels to the right, traversing 1 unit of the horizontal axis in each 1/2u generations, where u is the mutation rate. The smaller the initial population, the steeper will be the leading face of the wave. The larger the increase in population size, the smaller will be the distribution's vertical intercept. The implications of continued exponential growth are indistinguishable from those of a sudden burst of population growth Bottlenecks in population size also generate waves similar to those produced by a sudden expansion, but with elevated uppertail probabilities. Reductions in population size initially generate L-shaped distributions with high probability of identity, but these converge rapidly to a new equilibrium. In equilibrium populations the theoretical curves are free of waves. However, computer simulations of such populations generate empirical distributions with many peaks and little resemblance to the theory. On the other hand, agreement is better in the transient (nonequilibrium) case, where simulated empirical distributions typically exhibit waves very similar to those predicted by theory. Thus, waves in empirical distributions may be rich in information about the history of population dynamics.

Biological Evolution

Doubts about isonymy.

The method of isonymy, developed by Crow and Mange for estimating inbreeding from surname frequencies, requires an assumption that has not been appreciated: It is necessary to assume that all males in some ancestral generation, the founding stock, had unique surnames. Because this assumption is seldom justified in real populations, the applicability of the isonymy method is extremely limited. Even worse, the estimates it provides refer to an unspecified founding stock, and this implies that these estimates are devoid of information.

Consanguinity

Three components of genetic drift in subdivided populations.

Wright's metaphor of sampling is extended to consider three components of genetic drift: those occurring before, during, and after migration. To the extent that drift at each stage behaves like an independent random sample, the order of events does not matter. When sampling is not random, the order does matter, and the effect of population size is confounded with that of mobility. The widely cited result that genetic differentiation of local groups depends only on the product of group size and migration rate holds only when nonrandom sampling does not occur prior to migration in the life cycle.

Gene Frequency

Statistical analysis of the migration component of genetic drift.

Statistical methods are introduced for analysis of the migration component of genetic drift, i.e., of the stochastic changes that affect allele frequencies during migration between local groups. Attention focuses on alpha M, a parameter that measures the extent to which this component of drift departs from the ideal of independent random sampling, and which can be interpreted as a measure of the extent to which migration is kin-structured. It is shown that alpha M can be estimated from genetic data, even in the absence of information about the genealogical relationships of migrants, and Monte-Carlo simulations are used to approximate the sampling distribution of the estimator under the null hypothesis of independent random sampling. Application of these methods to data from the Aland Islands, Finland, shows that the migration pattern there is consistent with the hypothesis of independent random sampling.

Finland

The effect of non-random migration on genetic differences between populations.

Models of genetic population structure generally assume that emigrants from each local group are drawn at random from the set of individuals born there. We show that small violations of this assumption can have disproportionately large effects on genetic population structure, and we introduce a statistical method for measuring this effect.

Finland

Correlations between relatives in small populations.

Correlations between relatives in small, closed populations can be substantially smaller than predicted by the classical formulas of population genetics. This effect is especially pronounced for relatives whose most recent common ancestor is several generations removed. When the effective population size is small, correlations between even close relatives can be negative. This implies that in small populations conventional estimators of quantitative genetics parameters will be biased and that preferential treatment of close relatives will be less likely to evolve.

Gene Frequency