scholarly journals Geographical patterns of gene frequencies in Italian populations of Ornithogalum montanum (Liliaceae)

1991 ◽  
Vol 58 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Massimo Pigliucci ◽  
Guido Barbujani
Keyword(s):  
Gene Frequency ◽  
Genetic Relationships ◽  
Environmental Parameter ◽  
Allele Frequencies ◽  
Population Subdivision ◽  
Restricted Gene Flow ◽  
Frequency Change ◽  
Gene Frequencies ◽  
Unit Distance ◽  
Geographical Patterns

SummaryGeographic variation was studied at 15 electrophoretic loci (40 alleles) in Italian populations of Ornithogalum montanum Cyr. ex Ten. (Liliaceae). Homogeneity of allele frequencies was assessed by G tests; gene-frequency patterns were described by spatial autocorrelation statistics; matrices of genetic and environmental distance were compared through a series of Mantel's tests, and the zones of highest overall gene-frequency change per unit distance (steep multi-locus clines, or genetic boundaries) were identified. Nineteen allele frequencies appear heterogeneously distributed, but only 3 of them show significant spatial structure. Only 2 allele frequencies are correlated with 1 environmental parameter. Large genetic differences are observed between spatially close populations. These findings support a model of differentiation in which the genetic relationships between isolates do not depend on their spatial distances, but reflect mainly population subdivision and restricted gene flow.

scholarly journals SIMULATION OF X-LINKED SELECTION IN DROSOPHILA

Genetics ◽  
1976 ◽  
Vol 83 (3) ◽  
pp. 551-571
Author(s):  
Philip W Hedrick
Keyword(s):  
Gene Frequency ◽  
Frequency Change ◽  
Wild Type ◽  
Weak Selection ◽  
Gene Frequencies ◽  
Linked Gene ◽  
Males And Females ◽  
Genetic Simulation ◽  
Linked Selection ◽  
Best Fit

ABSTRACT The change in gene frequency for two X-linked mutants, y and w, in a number of experiments was compared to that predicted from a genetic simulation program which utilized estimated differences in relative mating ability, fecundity, and viability. The simulation gave excellent predictions of gene frequency change even when experiments were started with different initial gene frequencies in the males and females or when the two loci were segregating simultaneously. The rate of elimination was slower when there were unequal initial gene frequencies than when males and females had equal initial gene frequencies. Simulation demonstrated that this was a general phenomenon when there is strong selection but that the opposite is true for weak selection. In two other experiments, the mating advantage of wild-type males was balanced by a fecundity advantage in mutant females. In all four replicates of both experiments, the mutant was maintained for several generations at the high initial frequency but then decreased quickly and was eliminated. Results obtained restarting one of these experiments with flies from a generation after the decline in gene frequency indicated that a linked gene and not frequency-dependent selection was responsible for the unpredictable gene-frequency change in the mutant. Using a least squares technique, it was found that a recessive fecundity locus 15 map units from the w locus gave the best fit for bothexperiments.

scholarly journals A MARKOV PROCESS OF GENE FREQUENCY CHANGE IN A GEOGRAPHICALLY STRUCTURED POPULATION

Genetics ◽  
1974 ◽  
Vol 76 (2) ◽  
pp. 367-377
Author(s):  
Takeo Maruyama
Keyword(s):  
Genetic Variation ◽  
Markov Process ◽  
Diffusion Process ◽  
Gene Frequency ◽  
Transition Probabilities ◽  
Large Population ◽  
Sample Path ◽  
Time Parameter ◽  
Frequency Change ◽  
Structured Population

ABSTRACT A Markov process (chain) of gene frequency change is derived for a geographically-structured model of a population. The population consists of colonies which are connected by migration. Selection operates in each colony independently. It is shown that there exists a stochastic clock that transforms the originally complicated process of gene frequency change to a random walk which is independent of the geographical structure of the population. The time parameter is a local random time that is dependent on the sample path. In fact, if the alleles are selectively neutral, the time parameter is exactly equal to the sum of the average local genetic variation appearing in the population, and otherwise they are approximately equal. The Kolmogorov forward and backward equations of the process are obtained. As a limit of large population size, a diffusion process is derived. The transition probabilities of the Markov chain and of the diffusion process are obtained explicitly. Certain quantities of biological interest are shown to be independent of the population structure. The quantities are the fixation probability of a mutant, the sum of the average local genetic variation and the variation summed over the generations in which the gene frequency in the whole population assumes a specified value.

Population Subdivision and Molecular Sequence Variation: Theory and Analysis of Drosophila ananassae Data

Genetics ◽  
2003 ◽  
Vol 165 (3) ◽  
pp. 1385-1395
Author(s):  
Claus Vogl ◽  
Aparup Das ◽  
Mark Beaumont ◽  
Sujata Mohanty ◽  
Wolfgang Stephan
Keyword(s):  
Sequence Data ◽  
Isolation By Distance ◽  
Allele Frequencies ◽  
Drosophila Ananassae ◽  
Population Subdivision ◽  
Variation Theory ◽  
Peripheral Populations ◽  
Molecular Variation ◽  
Data Set ◽  
Evolutionary Forces

Abstract Population subdivision complicates analysis of molecular variation. Even if neutrality is assumed, three evolutionary forces need to be considered: migration, mutation, and drift. Simplification can be achieved by assuming that the process of migration among and drift within subpopulations is occurring fast compared to mutation and drift in the entire population. This allows a two-step approach in the analysis: (i) analysis of population subdivision and (ii) analysis of molecular variation in the migrant pool. We model population subdivision using an infinite island model, where we allow the migration/drift parameter 0398; to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of 0398;, we use a coalescence approach, implemented via a Markov chain Monte Carlo (MCMC) integration method that allows estimation of allele frequencies in the migrant pool. The second step of this approach (analysis of molecular variation in the migrant pool) uses the estimated allele frequencies in the migrant pool for the study of molecular variation. We apply this method to a Drosophila ananassae sequence data set. We find little indication of isolation by distance, but large differences in the migration parameter among populations. The population as a whole seems to be expanding. A population from Bogor (Java, Indonesia) shows the highest variation and seems closest to the species center.

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 Methods for Estimating Gene Frequencies and Detecting Selection in Bacterial Populations

Genetics ◽  
2000 ◽  
Vol 155 (2) ◽  
pp. 499-508 ◽  
Author(s):  
Bruce Rannala ◽  
Wei-Gang Qiu ◽  
Daniel E Dykhuizen
Keyword(s):  
Ixodes Scapularis ◽  
Balancing Selection ◽  
Surface Protein ◽  
Allele Frequencies ◽  
Gene Frequencies ◽  
Bacterial Populations ◽  
Polymerase Chain ◽  
Host Infection ◽  
Infinite Alleles Model

Abstract Recent breakthroughs in molecular technology, most significantly the polymerase chain reaction (PCR) and in situ hybridization, have allowed the detection of genetic variation in bacterial communities without prior cultivation. These methods often produce data in the form of the presence or absence of alleles or genotypes, however, rather than counts of alleles. Using relative allele frequencies from presence-absence data as estimates of population allele frequencies tends to underestimate the frequencies of common alleles and overestimate those of rare ones, potentially biasing the results of a test of neutrality in favor of balancing selection. In this study, a maximum-likelihood estimator (MLE) of bacterial allele frequencies designed for use with presence-absence data is derived using an explicit stochastic model of the host infection (or bacterial sampling) process. The performance of the MLE is evaluated using computer simulation and a method is presented for evaluating the fit of estimated allele frequencies to the neutral infinite alleles model (IAM). The methods are applied to estimate allele frequencies at two outer surface protein loci (ospA and ospC) of the Lyme disease spirochete, Borrelia burgdorferi, infecting local populations of deer ticks (Ixodes scapularis) and to test the fit to a neutral IAM.

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 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.

scholarly journals Genetic relationships of Amaurobioides (Anyphaenidae) spiders from the southeastern coast of New Zealand

Zootaxa ◽  
2007 ◽  
Vol 1425 (1) ◽  
pp. 1-10 ◽  
Author(s):  
BRENT D. OPELL ◽  
ANDREA M. BERGER ◽  
SOPHIA M. BOUS ◽  
MICHAEL L. MANNING
Keyword(s):  
Mitochondrial Dna ◽  
Haplotype Analysis ◽  
Genetic Relationships ◽  
Genetic Distances ◽  
Restricted Gene Flow ◽  
Long Distance Dispersal ◽  
Long Distance ◽  
Morphological Species ◽  
Southern Species ◽  
Northeastern Coast

Members of the genus Amaurobioides construct silk retreats in rock crevices of the marine spray zone, a harsh and unusual habitat for spiders. This study expands the distribution records of three morphological species of Amaurobioides found on the eastern and southern coasts of New Zealand’s South Island and uses mitochondrial DNA to examine their relationships and characterize their dispersal capabilities. Both 16S and ND1 sequences distinguish A. pletus found on the northeastern coast from a complex of two southern species comprised of A. maritimus from the mainland and A. picunus from Stewart Island. Neither 16S DNA nor ND1 protein separates these southern species. However, ND1 parsimony and likelihood analyses place 10 of 11 Stewart Island specimens in a clade of low support that nests deeply within A. maritimus. A nested haplotype analysis characterizes A. maritimus and A. picunus populations as having restricted gene flow/dispersal but with some long distance dispersal. Genetic distances between A. pletus and the A. maritimus-A. picunus complex indicate a Pliocene origin, whereas distances between A. maritimus and A. picunus suggest a Pleistocene divergence.

scholarly journals The use of selection experiments for detecting quantitative trait loci

1997 ◽  
Vol 69 (3) ◽  
pp. 227-232 ◽  
Author(s):  
L. OLLIVIER ◽  
L. A. MESSER ◽  
M. F. ROTHSCHILD ◽  
C. LEGAULT
Keyword(s):  
Quantitative Trait ◽  
Marker Locus ◽  
Frequency Change ◽  
Gene Frequencies ◽  
Marker Allele ◽  
Gene Effects ◽  
Selection Experiments ◽  
Frequency Changes ◽  
Combined Selection ◽  
Number Of Individuals

Gene frequency changes following selection may reveal the existence of gene effects on the trait selected. Loci for the selected quantitative trait (SQTL) may thus be detected. Additionally, one can estimate the average effect (α) of a marker allele associated with an SQTL from the allele frequency change (Δq) due to selection of given intensity (i). In a sample of unrelated individuals, it is optimal to select the upper and lower 27% for generating Δq in order to estimate α. For a given number of individuals genotyped, this estimator is 0·25i2 times more efficient than the classical estimator of α, based on the regression of the trait on the genotype at the marker locus. The method is extended to selection criteria using information from relatives, showing that combined selection considerably increases the efficiency of estimation for traits of low heritability. The method has been applied to the detection of SQTL in a selection experiment in which the trait selected was pig litter size averaged over the first four parities, with i=3. Results for four genes are provided, one of which yielded a highly significant effect. The conditions required for valid application of the method are discussed, including selection experiments over several generations. Additional advantages of the method can be anticipated from determining gene frequencies on pooled samples of blood or DNA.

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