The geometry of random drift III. Recombination and diffusion

1977 ◽  
Vol 9 (2) ◽  
pp. 260-267 ◽  
Author(s):  
Peter L. Antonelli ◽  
Kenneth Morgan ◽  
G. Mark Lathrop
Keyword(s):  
Velocity Field ◽  
Markov Chains ◽  
Genetic Drift ◽  
Present Model ◽  
Random Mating ◽  
Recombination Fraction ◽  
Random Genetic Drift ◽  
Random Drift ◽  
Intrinsic Geometry ◽  
And Diffusion

A new diffusion model for random genetic drift of a two-locus di-allelic system is proposed. The Christoffel velocity field and the intrinsic geometry of the diffusion is computed for the equilibrium surface. It is seen to be radically non-spherical and to depend explicitly on the recombination fraction. The model has not been shown to be a limit of discrete Markov chains. For large values of the recombination, the present model is radically different from that of Ohta and Kimura, which is an approximation to the discrete process of random mating in the limit as the value of the recombination fraction goes to zero.

The geometry of random drift III. Recombination and diffusion

1977 ◽  
Vol 9 (02) ◽  
pp. 260-267 ◽  
Author(s):  
Peter L. Antonelli ◽  
Kenneth Morgan ◽  
G. Mark Lathrop
Keyword(s):  
Velocity Field ◽  
Markov Chains ◽  
Genetic Drift ◽  
Present Model ◽  
Random Mating ◽  
Recombination Fraction ◽  
Random Genetic Drift ◽  
Random Drift ◽  
Intrinsic Geometry ◽  
And Diffusion

A new diffusion model for random genetic drift of a two-locus di-allelic system is proposed. The Christoffel velocity field and the intrinsic geometry of the diffusion is computed for the equilibrium surface. It is seen to be radically non-spherical and to depend explicitly on the recombination fraction. The model has not been shown to be a limit of discrete Markov chains. For large values of the recombination, the present model is radically different from that of Ohta and Kimura, which is an approximation to the discrete process of random mating in the limit as the value of the recombination fraction goes to zero.

The geometry of random drift II. The symmetry of random genetic drift

1977 ◽  
Vol 9 (2) ◽  
pp. 250-259 ◽  
Author(s):  
Peter L. Antonelli ◽  
Jared Chapin ◽  
G. Mark Lathrop ◽  
Kenneth Morgan
Keyword(s):  
Velocity Field ◽  
Genetic Drift ◽  
Gene Frequency ◽  
Radial Symmetry ◽  
Divergence Times ◽  
Random Genetic Drift ◽  
Initial State ◽  
Random Drift ◽  
Arithmetic Average ◽  
Frequency Space

It has been conjectured that a certain transformation of gene frequency space due to Fisher and Bhattacharyya will map the random genetic drift process, or its diffusion approximation, into one with radial symmetry. This paper proves rigorously that the Fisher–Bhattacharyya mapping does not do this. This implies that the initial state of an evolving ensemble can only be unbiasedly estimated from the means of a sample if we weight by the proper divergence times. If the ensemble is known not to have begun at the centroid of frequency space, the estimate of the initial state vector is not simply the arithmetic average, as symmetry analysis of the Christoffel velocity field shows.

The geometry of random drift II. The symmetry of random genetic drift

1977 ◽  
Vol 9 (02) ◽  
pp. 250-259 ◽  
Author(s):  
Peter L. Antonelli ◽  
Jared Chapin ◽  
G. Mark Lathrop ◽  
Kenneth Morgan
Keyword(s):  
Velocity Field ◽  
Genetic Drift ◽  
Gene Frequency ◽  
Radial Symmetry ◽  
Divergence Times ◽  
Random Genetic Drift ◽  
Initial State ◽  
Random Drift ◽  
Arithmetic Average ◽  
Frequency Space

It has been conjectured that a certain transformation of gene frequency space due to Fisher and Bhattacharyya will map the random genetic drift process, or its diffusion approximation, into one with radial symmetry. This paper proves rigorously that the Fisher–Bhattacharyya mapping does not do this. This implies that the initial state of an evolving ensemble can only be unbiasedly estimated from the means of a sample if we weight by the proper divergence times. If the ensemble is known not to have begun at the centroid of frequency space, the estimate of the initial state vector is not simply the arithmetic average, as symmetry analysis of the Christoffel velocity field shows.

Mutational order: a major stochastic process in evolution

1990 ◽  
Vol 240 (1297) ◽  
pp. 29-37 ◽  
Keyword(s):  
Stochastic Process ◽  
Computer Simulations ◽  
Genetic Drift ◽  
Molecular Clock ◽  
Quantitative Character ◽  
Evolutionary Divergence ◽  
Random Genetic Drift ◽  
Random Drift ◽  
Large Populations ◽  
Different Populations

Computer simulations in which selection acts on a quantitative character show that the randomness of mutations can contribute significantly to evolutionary divergence between populations. In different populations, different advantageous mutations occur, and are selected to fixation, so that the populations diverge even when they are initially identical, and are subject to identical selection. This stochastic process is distinct from random genetic drift. In some circumstances (large populations or strong selection, or both) mutational order can be greatly more important than random drift in bringing about divergence. It can generate a ‘disconnection’ between evolution at the phenotypic and genotypic levels, and can give rise to a rough ‘molecular clock’, albeit episodic, that is driven by selection. In the absence of selection, mutational order has little or no effect.

scholarly journals Linkage disequilibrium due to random genetic drift

1969 ◽  
Vol 13 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Tomoko Ohta ◽  
Motoo Kimura
Keyword(s):  
Stochastic Process ◽  
Linkage Disequilibrium ◽  
Genetic Drift ◽  
Recombination Fraction ◽  
Random Genetic Drift ◽  
Effective Population ◽  
Finite Populations ◽  
Population Number ◽  
Backward Equation ◽  
Expected Values

The behaviour of linkage disequilibrium between two segregating loci in finite populations has been studied as a continuous stochastic process for different intensity of linkage, assuming no selection. By the method of the Kolmogorov backward equation, the expected values of the square of linkage disequilibrium z2, and other two quantities, xy(1 − x) (1 − y) and z(1 − 2x) (1 − 2y), were obtained in terms of T, the time measured in Ne as unit, and R, the product of recombination fraction (c) and effective population number (Ne). The rate of decrease of the simultaneous heterozygosity at two loci and also the asymptotic rate of decrease of the probability for the coexistence of four gamete types within a population were determined. The eigenvalues λ1, λ2 and λ3 related to the stochastic process are tabulated for various values of R = Nec.

CYTO-NUCLEAR EPISTASIS: TWO-LOCUS RANDOM GENETIC DRIFT IN HERMAPHRODITIC AND DIOECIOUS SPECIES

Evolution ◽  
2006 ◽  
Vol 60 (4) ◽  
pp. 643 ◽  
Author(s):  
Michael J. Wade ◽  
Charles J. Goodnight
Keyword(s):  
Genetic Drift ◽  
Random Genetic Drift ◽  
Dioecious Species

scholarly journals Influence of Random Genetic Drift on Human Immunodeficiency Virus Type 1envEvolution During Chronic Infection

Genetics ◽  
2004 ◽  
Vol 166 (3) ◽  
pp. 1155-1164 ◽  
Author(s):  
Daniel Shriner ◽  
Raj Shankarappa ◽  
Mark A. Jensen ◽  
David C. Nickle ◽  
John E. Mittler ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Human Immunodeficiency Virus Type ◽  
Virus Type ◽  
Genetic Drift ◽  
Chronic Infection ◽  
Random Genetic Drift ◽  
Immunodeficiency Virus

NUMERICAL ANALYSIS OF RANDOM DRIFT IN A CLINE

Genetics ◽  
1980 ◽  
Vol 94 (2) ◽  
pp. 497-517
Author(s):  
Thomas Nagylaki ◽  
Bradley Lucier
Keyword(s):  
Natural Populations ◽  
The Other ◽  
Random Genetic Drift ◽  
Gene Frequencies ◽  
Random Drift ◽  
Linear Habitat ◽  
Asymptotic Formulae ◽  
A Chain ◽  
Average Position ◽  
Uniform Population

ABSTRACT The equilibrium state of a diffusion model for random genetic drift in a cline is analyzed numerically. The monoecious organism occupies an unbounded linear habitat with constant, uniform population density. Migration is homogeneouq symmetric and independent of genotype. A single diallelic locus with a step environment is investigated in the absence of dominance and mutation. The flattening of the expected cline due to random drift is very slight in natural populations. The ratio of the variance of either gene frequency to the product of the expected gene frequencies decreases monotonically to a nonzero constant. The correlation between the gene frequencies at two points decreases monotonically to zero as the separation is increased with the average position fixed; the decrease is asymptotically exponential. The correlation decreases monotonically to a positive constant depending on the separation as the average position increasingly deviates from the center of the cline with the separation fixed. The correlation also decreases monotonically to zero if one of the points is fixed and the other is moved outward in the habitat, the ultimate decrease again being exponential. Some asymptotic formulae are derived analytically.—The loss of an allele favored in an environmental pocket is investigated by simulating a chain of demes exchanging migrants, the other assumptions being the same as above. For most natural populations, provided the allele would be maintained in the population deterministically, this process is too slow to have evolutionary importance.

scholarly journals A General Solution of the Wright–Fisher Model of Random Genetic Drift

2016 ◽  
Vol 27 (4) ◽  
pp. 467-492 ◽  
Author(s):  
Tat Dat Tran ◽  
Julian Hofrichter ◽  
Jürgen Jost
Keyword(s):  
General Solution ◽  
Genetic Drift ◽  
Random Genetic Drift ◽  
Fisher Model

scholarly journals Evolution of gene regulatory networks by means of selection and random genetic drift

2018 ◽  
Author(s):  
Antonios Kioukis ◽  
Pavlos Pavlidis
Keyword(s):  
Natural Selection ◽  
Positive Selection ◽  
Genetic Drift ◽  
Regulatory Networks ◽  
Fitness Landscape ◽  
Random Genetic Drift ◽  
Maturation Period ◽  
Evolutionary Forces ◽  
Gene Regulatory

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. Furthermore, it is not known if existing tools that identify recent and strong positive selection from genomic sequences, in simple models of evolution, can detect recent positive selection when it operates on GRNs. Here, we propose a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. Since the population size is finite, random genetic drift is explicitly applied. The fitness of a mutation is not constant, but we evaluate the fitness of each individual by measuring its genetic distance from an optimal genotype. Mutations and recombination may take place from generation to generation, modifying the genotypic composition of the population. Each individual goes through a maturation period, where its GRN reaches equilibrium. At the next step, individuals compete to produce the next generation. As time progresses, the beneficial genotypes push the population higher in the fitness landscape. We examine properties of the GRN evolution such as robustness against the deleterious effect of mutations and the role of genetic drift. We confirm classical results from Andreas Wagner’s work that GRNs show robustness against mutations and we provide new results regarding the interplay between random genetic drift and natural selection.

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