scholarly journals The average number and the variance of generations at particular gene frequency in the course of fixation of a mutant gene in a finite population

1972 ◽  
Vol 19 (2) ◽  
pp. 109-113 ◽  
Author(s):  
Takeo Maruyama
Keyword(s):  
Computer Simulations ◽  
Diffusion Approximation ◽  
Gene Frequency ◽  
Finite Population ◽  
Mutant Gene ◽  
Gene Frequencies ◽  
Explicit Formulas ◽  
Two Generations

SUMMARYIn the case of an allele which is going to become fixed in a population, the average number of generations for which the population assumes particular gene frequencies is investigated, using the diffusion approximation. Explicit formulas were obtained and they were checked by computer simulations. As a particular case, it is shown that if a new mutant that is selectively neutral is eventually fixed in a population of size N, it spends two generations on average at each of the intermediate frequencies (1/2N, 2/2N, …, (2N−1)/2N), and the variance at each frequency is four generations.

scholarly journals A comparison of two methods for predicting changes in the distribution of gene frequency when selection is applied repeatedly to a finite population

1969 ◽  
Vol 13 (2) ◽  
pp. 117-126 ◽  
Author(s):  
Derek J. Pike
Keyword(s):  
Iterative Procedure ◽  
Gene Frequency ◽  
Finite Population ◽  
Transition Matrices ◽  
Single Cycle ◽  
Gene Frequencies ◽  
Mean And Variance ◽  
The Mean ◽  
The One ◽  
Selection Of

Robertson (1960) used probability transition matrices to estimate changes in gene frequency when sampling and selection are applied to a finite population. Curnow & Baker (1968) used Kojima's (1961) approximate formulae for the mean and variance of the change in gene frequency from a single cycle of selection applied to a finite population to develop an iterative procedure for studying the effects of repeated cycles of selection and regeneration. To do this they assumed a beta distribution for the unfixed gene frequencies at each generation.These two methods are discussed and a result used in Kojima's paper is proved. A number of sets of calculations are carried out using both methods and the results are compared to assess the accuracy of Curnow & Baker's method in relation to Robertson's approach.It is found that the one real fault in the Curnow-Baker method is its tendency to fix too high a proportion of the genes, particularly when the initial gene frequency is near to a fixation point. This fault is largely overcome when more individuals are selected. For selection of eight or more individuals the Curnow-Baker method is very accurate and appreciably faster than the transition matrix method.

scholarly journals A note on the diffusion approximation for the variance of the number of generations until fixation of a neutral mutant gene

1970 ◽  
Vol 15 (2) ◽  
pp. 251-255 ◽  
Author(s):  
P. Narain
Keyword(s):  
Population Size ◽  
General Expression ◽  
Diffusion Approximation ◽  
Finite Population ◽  
Mutant Gene ◽  
Matrix Methods ◽  
Neutral Gene

SUMMARYA general expression is derived for the variance of time to fixation of a neutral gene in a finite population using a diffusion approximation. The results are compared with exact values derived by matrix methods for a population size of 8.

scholarly journals On sojourn times at particular gene frequencies

1975 ◽  
Vol 25 (2) ◽  
pp. 89-94 ◽  
Author(s):  
Edward Pollak ◽  
Barry C. Arnold
Keyword(s):  
Markov Chains ◽  
Gene Frequency ◽  
Overlapping Generations ◽  
Finite Population ◽  
Diffusion Method ◽  
Gene Frequencies ◽  
Sojourn Times ◽  
The Mean ◽  
Number Of Visits ◽  
Finite Markov Chains

SUMMARYThe distribution of visits to a particular gene frequency in a finite population of size N with non-overlapping generations is derived. It is shown, by using well-known results from the theory of finite Markov chains, that all such distributions are geometric, with parameters dependent only on the set of bij's, where bij is the mean number of visits to frequency j/2N, given initial frequency i/2N. The variance of such a distribution does not agree with the value suggested by the diffusion method. An improved approximation is derived.

scholarly journals GENETIC VARIATION IN A HETEROGENEOUS ENVIRONMENT. I. TEMPORAL HETEROGENEITY AND THE ABSOLUTE DOMINANCE MODEL

Genetics ◽  
1974 ◽  
Vol 78 (2) ◽  
pp. 757-770
Author(s):  
Philip W Hedrick
Keyword(s):  
Genetic Variation ◽  
Temporal Variation ◽  
Gene Frequency ◽  
Environmental Heterogeneity ◽  
Finite Population ◽  
Environmental Variation ◽  
Dominance Model ◽  
Infinite Population ◽  
The Absolute ◽  
Absolute Dominance

ABSTRACT The conditions for a stable polymorphism and the equilibrium gene frequency in an infinite population are compared when there is spatial or temporal environmental heterogeneity for the absolute dominance model. For temporal variation the conditions for stability are more restrictive and the equilibrium gene frequency is often at a low gene frequency. In a finite population, temporal environmental heterogeneity for the absolute dominance model was found to be quite ineffective in maintaining genetic variation and is often less effective than no selection at all. For comparison, the maximum maintenance for temporal variation is related to the overdominant model. In general, cyclic environmental variation was found to be more effective at maintaining genetic variation than where the environment varies stochastically. The importance of temporal environmental variation and the maintenance of genetic variation is discussed.

scholarly journals Some observations on asymmetrical correlated responses to selection

1966 ◽  
Vol 7 (1) ◽  
pp. 44-57 ◽  
Author(s):  
B. B. Bohren ◽  
W. G. Hill ◽  
A. Robertson
Keyword(s):  
Model Selection ◽  
Gene Frequency ◽  
Genetic Parameters ◽  
Correlated Response ◽  
Correlated Responses ◽  
Gene Frequencies ◽  
Genetic Covariance ◽  
Gene Effects ◽  
Selection Experiments ◽  
Relative Change

The pattern of changes of the genetic covariance between two characters on selection was examined in an effort to explain the asymmetry of correlated responses in two traits, or of the same trait in two environments, frequently observed in experimental results.The algebraic conclusions were further examined by model selection experiments using a computer. The computer was programmed to calculate the change in gene frequency from generation to generation and to calculate from it the expected changes in genetic variances and covariance as selection proceeded. This procedure was carried out with several models of gene effects and gene frequencies.Asymmetry of the genetic covariance, and consequently of the correlated responses, resulted when the relative change in gene frequency at the loci contributing positively and negatively to the covariance depended on the trait selected. The conditions necessary for the development of asymmetry were examined and the results suggest that any symmetry found in an experiment is perhaps more surprising than asymmetry. Probably the most frequent contribution to asymmetry in practice will be from loci contributing negatively to the covariance and having frequencies other than 0·5.Accurate prediction of correlated response over many generations is therefore not possible without prior knowledge of the composition of the genetic covariance, as well as its magnitude. The validity of existing theory for the prediction of correlated responses is likely to be much poorer than for the prediction of direct responses. Predictions would then have to be based on the genetic parameters estimated in each generation.

Stepping stone models of finite length

1970 ◽  
Vol 2 (02) ◽  
pp. 229-258 ◽  
Author(s):  
Takeo Maruyama
Keyword(s):  
Monte Carlo ◽  
Population Structure ◽  
Finite Length ◽  
Correlation Coefficients ◽  
Gene Frequencies ◽  
Explicit Formulas ◽  
Stepping Stone ◽  
Monte Carlo Experiments ◽  
Stepping Stone Models ◽  
Stepping Stone Model

The stepping stone model of population structure, of finite length, is analysed with special reference to the variance, and correlation coefficients of gene frequencies. Explicit formulas for these quantities are obtained. The model is also analysed for the genetic variability maintained in the population. In order to check the validity of the analytical results, several numerical computations were carried out using two different methods: iterations and Monte Carlo experiments. The values obtained by these numerical methods agree well with the theoretical values obtained by formulas derived analytically.

DIFFUSION OF A POPULATION OF INTERACTING REPLICATORS IN SEQUENCE SPACE

2002 ◽  
Vol 05 (04) ◽  
pp. 457-461 ◽  
Author(s):  
BÄRBEL M. R. STADLER
Keyword(s):  
Simple Model ◽  
Population Size ◽  
Computer Simulations ◽  
Mutation Rate ◽  
Sequence Space ◽  
Finite Population ◽  
Fitness Landscape ◽  
Diffusion Constant ◽  
Sequence Length

We consider a simple model for catalyzed replication. Computer simulations show that a finite population moves in sequence space by diffusion analogous to the behavior of a quasispecies on a flat fitness landscape. The diffusion constant depends linearly on the per position mutation rate and the ratio of sequence length and population size.

scholarly journals DYNAMICS OF THE LINKAGE DISEQUILIBRIUM FUNCTION UNDER MODELS OF GENE-FREQUENCY HITCHHIKING

Genetics ◽  
1981 ◽  
Vol 99 (2) ◽  
pp. 337-356
Author(s):  
Marjorie A Asmussen ◽  
Michael T Clegg
Keyword(s):  
Linkage Disequilibrium ◽  
Gene Frequency ◽  
Initial Conditions ◽  
Recombination Fraction ◽  
Qualitative Description ◽  
Selection Intensity ◽  
Gene Frequencies ◽  
Dependent Behavior ◽  
Wide Range ◽  
Over Time

ABSTRACT The dynamic behavior of the linkage disequilibrium (D) between a neutral and a selected locus is analyzed for a variety of deterministic selection models. The time-dependent behavior of D is governed by the gene frequency at the selected locus (p) and by the selection (s) and recombination (r) parameters. Thomson (1977) showed numerically that D may increase under certain initial conditions. We give exact conditions for D to increase in time, which require that the selection intensity exceed the recombination fraction (s > r) and that p be near zero or one. We conclude from this result that gene frequency hitchhiking is most likely to be important when a new favorable mutant enters a population. We also show that, for what can be a wide range of gene frequencies, D will decay at a faster rate than the neutral rate. Consequently, the hitchhiking effect may quickly diminish as the selected gene becomes more common.—The method of analysis allows a complete qualitative description of the dynamics of D as a function of s and r. Two major findings concern the range of gene frequencies at the selected locus for which D either increases over time or decays at a faster rate than under neutrality. For all models considered, the region where D increases (i) first enlarges then shrinks as selection intensifies, and (ii) steadily shrinks as r increases. In contrast, the region of accelerated decay constantly enlarges as the selection intensity increases. This region will either shrink or enlarge as r increases, depending upon the form of selection in force.

scholarly journals Effects of dominance and size of population on response to mass selection

1961 ◽  
Vol 2 (2) ◽  
pp. 177-188 ◽  
Author(s):  
Ken-Ichi Kojima
Keyword(s):  
Gene Frequency ◽  
Finite Size ◽  
Prediction Equation ◽  
Small Population ◽  
Mass Selection ◽  
Gene Frequencies ◽  
Random Drift ◽  
Expected Gain ◽  
The Mean ◽  
Frequency Changes

A theory of mass selection in a small population was developed, and the mean change in gene frequencies, the variance of gene frequency changes and the expected gain in the mean phenotypic value of an offspring population were formulated in terms of a generalized selection differential and the additive and dominance effects of genes.The magnitude of the variance of changes in gene frequency was compared with the magnitude of the variance expected from the genetic random drift in a population with the same gene frequency and of the same size in absence of selection. The former was found to be usually smaller than the latter when the gene frequency ranged from intermediate to high and when selection was directed for a high performance.The usual prediction equation for gain from selection in an infinite population was compared with the expected gain formula derived for a small population. The size of the population did not cause a serious difference between the two expected gains when there was no dominance effect of genes. Dominance alone could cause the usual prediction to be slightly more biased. The joint effects of the finite size of population and dominance gene action could amount to a considerable bias in the usual prediction equation. Such a bias can be, in the main, accounted for by the inbreeding depression.

Random selective advantages of a gene in a finite population

1969 ◽  
Vol 6 (1) ◽  
pp. 19-37 ◽  
Author(s):  
Louis Jensen ◽  
Edward Pollak
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Gene Frequency ◽  
Finite Population ◽  
Planck Equation ◽  
Kolmogorov Equation ◽  
Rigorous Derivation ◽  
Process Of Change ◽  
Second Moments ◽  
Image Position

A problem of interest to many population geneticists is the process of change in a gene frequency. A popular model used to describe the change in a gene frequency involves the assumption that the gene frequency is Markovian. The probabilities in a Markov process can be approximated by the solution of a partial differential equation known as the Fokker-Planck equation or the forward Kolmogorov equation. Mathematically this equation is where subscripts indicate partial differentiation. In this equation, f(p, x; t) is the probability density that the frequency of a gene is x at time t, given that the frequency was p at time t = o. The expressions MΔX and VΔx are, respectively, the first and second moments of the change in the gene frequency during one generation. A rigorous derivation of this equation was given by Kolmogorov (1931).

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