Malaria life cycle intensifies both natural selection and random genetic drift

In any finite genetic population, the effect of chance involved in the sampling by which one generation replaces another causes gene frequency change as long as fixation or extinction is not achieved. In genetic terminology this fluctuation in gene frequency due to the finiteness of a population is called 'random genetic drift'. Fisher (1922), using an equation of the diffusion type, was the first to make an effort to describe quantitatively the phenomenon of random genetic drift. In the corrected version of this work (1930), he found the general result that the rate of decrease of the genetic variance in the population due to drift was 1/(2N) per generation, where N is the number of individuals of mating potential. This result was confirmed by various authors using different methods (e.g. Wright, 1931, 1937; Malecot, 1944; Feller, 1950). The particular form of the diffusion model which has had the widest use was introduced into genetical literature by Wright (1945). This equation which plays a fundamental role in the theory of gene frequencies is the Kolmogorov forward equation or-as it is commonly known among physicists-the Fokker-Planck equation. Earlier Kolmogorov (1935) had introduced the steady-state form of the forward equation in genetics. The complete solutions to the problem, however, were obtained much later and are due to Kimura (1955, 1957). The problem of random genetic drift as a problem in finite Markov chains was first considered by Malecot (1944). Based on the largest non-unit characteristic root of the transition probability matrix Malecot obtained the asymptotic rate of decrease of heterozygosity. This is essentially the same as the previously known results due to Fisher and Wright for steady decay. Feller (1951) succeeded in finding a general expression for all the characteristic roots of the transition probability matrix. The use of diffusion approximations requires the assumption of an infinite population: while in fact the state space is discrete, it is treated as though it were continuous. The tacit assumption in such an approach is that for large population size the approximation of the discrete time, discrete space process by the continuous diffusion process does not result in serious error. It was only recently that a rigorous justification of the diffusion approach was given by Watterson (1962) with respect to the processes considered by Wright (1945) and Kimura (1954, 1955). The validity of the diffusion approximation as providing adequate numerical solution to the problem concerning the probability that a particular gene is lost or fixed by a certain time was one of the questions considered by Ewens (1963). Since exact expressions were not available his method of getting exact results consisted in simply powering the transition matrix using a high-speed computer and collecting the appropriate terms.

Evolutionary change can occur by nonadaptive processes, such as random genetic drift, and as a consequence of selection on linked genetic variants. In addition, if selective regimes change over time, an allele currently at a high frequency because of past fitness advantage may be suboptimal for its present environment. Small effective population size along the human lineage increased the influence of drift, rendering mutations with slight effects on fitness effectively neutral. Demographic events like spatial expansions and population bottlenecks shape most of the genetic variation within and among modern populations. Natural selection itself may also contribute to nonadaptive or maladaptive change by increasing the frequency of linked deleterious variants. Also, certain maladaptive alleles may have increased in frequency because of compensating fitness advantages they provide. Key Concepts: Reduced effective population size along the human lineage led to an increase in the influence of genetic drift and a reduction in the efficacy of natural selection, especially for mutations with small selective effects. Evidence for this can be seen in comparisons of measures of natural selection in lineages having different effective population sizes. Genome‐wide variation within and between human populations can be almost entirely explained by random drift and demographic forces other natural selection. Spatial expansions in human evolutionary history may cause gene surfing, in which low frequency alleles at the wave of advance can reach high frequencies and spread over large areas merely due to the effects of intense genetic drift. Nonadaptive gene surfing might be a better explanation than adaptive evolution for some high frequency, widespread genetic variants. Population bottlenecks in human evolutionary history can lead to increases in drift and reductions in the efficacy of purifying selection. This leads to an increase in the fraction of slightly deleterious mutations present in human populations that have experienced recent bottlenecks. Natural selection on alleles can result in nonadaptive shifts in the frequencies of alleles that are closely linked to them. Such linkage effects can lead to the increased frequencies of mildly deleterious alleles if they are linked to a beneficial variant, and can interfere with the effectiveness of adaptive evolution in promoting an advantageous allele if it is linked to a deleterious allele. Caution should be exercised in interpreting patterns of genetic variation in human populations as being adaptive without thoroughly ruling out nonadaptive explanations.

Natural selection causes gene frequency changes in a large population leading to genetic evolution over evolutionary time scales. Such gene frequency changes, however, involve an optimizing principle. According to Kimura, such changes, over a short interval of time, occur in a manner such that the increase in population fitness is maximum for a given distance between parent and daughter generation gene frequencies. But according to Ewens, of all gene frequency changes, including those that lead to the same partial increase in mean fitness as the natural selection gene frequency changes, the natural selection values minimize the generalized distance measure between parent and daughter generation gene frequency values. These two optimality principles happen to be mirror images of each other. However, the optimality principles are restricted to the case where the increase in mean fitness is to thefirst order in natural selection gene frequency changes. I show in this paper that, instead of linear approximation to the increase in mean fitness, the treatment can be fairly general, and the exact increase in mean fitness can be considered so as to include the dominance effects of the genes.

Stochastic models in population genetics which lead to diffusion equations are considered. A geometric formula for the asymptotic expansions of the fundamental solutions of these equations is presented. Specifically, the random genetic drift process of one-locus theory and the Ohta–Kimura model of two-locus di-allelic systems with linkage are studied. Agreement with the work of Keller and Voronka for the two-allele one-locus case is obtained. For the general n-allele problem, the formulas obtained here are apparently new.

Many vertebrates exhibit homing behavior during breeding migration. Such behavior is adaptive, obviously, if individuals reproduce most successfully in habitats where they themselves were spawned. Nevertheless, by reducing gene exchange among local breeding populations, homing behavior may have profound evolutionary consequences at the species level. Considerable divergence in allelic frequencies will develop by random genetic drift among geographically isolated demes or even over continuously distributed populations isolated by virtue of low dispersal and distance (Wright, 1931, 1943, 1951; Malecot, 1969). Moreover, natural selection may promote local adaptation and diversification of demes if unopposed by the homogenizing influence of interdemic gene flow (Ehrlich and Raven, 1969). Studies of genetic variation and population structure in animals with homing instincts, therefore, should yield insight into the process and mechanisms of evolutionary divergence among conspecific populations. How much divergence among demes is due to random genetic drift and how much is due to natural selection has proved difficult to evaluate. Because natural selection may act in a complex manner on complex phenotypes, general consequences of homing behavior on gene frequency distributions cannot be specified. On the other hand, frequency distributions of selectively neutral genes have been precisely stated for a number of applicable population models. Unfortunately, even these testable predictions depend on pa-

Selection variability for Arg48His in alcohol dehydrogenase ADH1B among Asian populations.

Reduced genetic diversity in a meiobenthic copepod exposed to a xenobiotic

P opulation genetics relies heavily on mathematical modeling to make quantitative predictions about the behavior of genes in populations. These models are based on the principles of classic Mendelian gene inheritance; the Hardy-Weinberg equilibrium law, which predicts the gene frequency in a population; and Darwin's theory of natural selection. PopGene version 1 is a simulation program that explores the parameters that affect the behavior of alternative forms of a gene (alleles) in a population. The program window is composed of three smaller windows specifying the parameters used, the calculated allele frequencies through each generation, and the graphical output of the calculations. PopGene provides simulations for both basic and more advanced models in population genetics. The simplest model demonstrates the principles of the Hardy-Weinberg equilibrium law for the case of a single gene with two alleles. Increasingly complex examples based on the assumptions of the Hardy-Weinberg equilibrium law demonstrate the effect of multiple alleles of a gene and multiple gene loci on the genotype of all the individuals in a population. Default parameters for each model are built into the program, but users may also enter their own values. The simulation results, parameters, and graphs may be saved or printed. Up to 15 simulations may be run for a particular model with the results plotted on a single graph for easy comparison. Natural selection and inbreeding can be studied with the program. Natural selection of a gene with two alleles occurs when the fitness of each genotype is not equal. The program permits users to examine the outcomes of several scenarios—selection of an allele that exhibits dominance over another, alleles that combine to produce an intermediate (semidominant) phenotype, an allele that is recessive to another, or selection against a recessive allele because of its lethality. The model for inbreeding explores the consequence of nonrandom mating between individuals on the genotype frequencies of that population. Mating pairings are included to demonstrate self-fertilization (the most extreme form of nonrandom mating), as well as matings between parent and offspring; matings between siblings, first cousins, and second cousins; and random mating. PopGene also provides simulations for genetic drift, mutation, and migration—factors that contribute to evolutionary changes in a population that have long-term effects and are more difficult to study. In summary, PopGene is a valuable tool to use in conjunction with traditional textbook-based teaching of an introductory population genetics course. It provides students with illustrations of the principles they have learned. The program is straightforward, easy to use, and is available for Macintosh and Windows platforms. No preprinted manual is available for PopGene; however, a concise and well-written one is supplied as a PDF file that is readable with Adobe Acrobat. It covers the specifics of using the program and provides a step-by-step tutorial. A brief summary of population genetics, mathematical modeling, and the value and limitations of computer simulations is also discussed. The system requires a PC with a 486 or Pentium processor that uses Windows 3.1, 95, 98, or NT with 8 MB RAM or any Macintosh with 4 MB RAM, a 1.4-MB disk drive, and a hard drive. PopGene Trinity Software, Inc. Plymouth, NH. $95.00; $39.95, college students. 800-352-1282

A modified Wright–Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity

The role of random genetic in the evolutionary process has, for about two decades, been one of the controversial issues in population genetics. Some authors have appealed to drift as a convenient explanation of the origin of differences among organisms for which no other explanations seemed to be available. But one's inability to discover the adaptive significance of a trait does not mean that it has none (cf. Dobzhansky, 1956). The hypothesis of random genetic should not be used as a loophole; to be accepted it requires a firmer basis than suspicion. Other authors seem to think that and natural selection are alternatives. As soon as a gene is shown to have any effect whatever on fitness, the conclusion is drawn that its distribution in populations must be determined solely by selection and cannot be influenced by random drift. But this is a logical non-sequitur. The important work of Aird et al. (1954) and of Clarke et al. (1956) disclosed that the incidence of certain types of gastrointestinal ulceration is significantly different in persons with different blood groups. This is, however, far from a convincing demonstration that the observed diversity in the frequencies of the blood group genes in human populations is governed wholly, or even partially, by selection for resistance to ulcers. To make such a conclusion tenable it would have to be demonstrated that the environments in which human racial differences have evolved actually favored greater resistance in certain parts of the

Although transcript-error rates are markedly higher than DNA-level mutation rates, a broad perspective on the degree to which they diverge across lineages remains to be developed. Using modified rolling-circle sequencing, we found a narrow range of transcript-error rates across the Tree of Life, with little evidence supporting local control of error rates associated with gene expression levels. Most errors result in missense changes if translated, and, as with a fraction of nonsense errors, these are underrepresented relative to random expectations, suggesting the existence of mechanisms for purging some such errors. To understand how natural selection and random genetic drift might shape transcript-error rates, we present a model based on cell biology and population genetics. However, while this framework helps understand the evolution of this highly conserved trait, as currently structured, it explains only 20% of the variation in the data, suggesting a need for further theoretical work in this area.

Natural selection

In order to clarify the mechanisms responsible for the observed linkage disequilibrium, such as that found between markers in the major histocompatibility complex of man and mouse, linkage disequilibrium between two linked loci was studied for a finite population with a subdivided structure. The infinite allele model was used. In analogy with the subdivision of the inbreeding coefficient, the linkage disequilibrium coefficient was subdivided, and various variance components of disequilibrium were defined. It was found that the disequilibrium components may get very large when migration is limited if the correlation of alleles at the two loci within a colony is taken relative to that of the entire population. In other words, with limited migration, random genetic drift of gamete types prevails in each colony. A possible test in which the variance components of disequilibrium are compared is suggested; the test discriminates between epistatic natural selection and limited migration, showing the former as the main cause of the observed linkage disequilibrium. It is pointed out that the major histocompatibility complex polymorphism is in accord with the population genetics model of multigene families that incorporate gene conversion or double unequal crossing-over between the loci in the supergene family.

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.

BackgroundGenome degradation of host-restricted mutualistic endosymbionts has been attributed to inactivating mutations and genetic drift while genes coding for host-relevant functions are conserved by purifying selection. Unlike their free-living relatives, the metabolism of mutualistic endosymbionts and endosymbiont-originated organelles is specialized in the production of metabolites which are released to the host. This specialization suggests that natural selection crafted these metabolic adaptations. In this work, we analyzed the evolution of the metabolism of the chromatophore of Paulinella chromatophora by in silico modeling. We asked whether genome reduction is driven by metabolic engineering strategies resulted from the interaction with the host. As its widely known, the loss of enzyme coding genes leads to metabolic network restructuring sometimes improving the production rates. In this case, the production rate of reduced-carbon in the metabolism of the chromatophore.ResultsWe reconstructed the metabolic networks of the chromatophore of P. chromatophora CCAC 0185 and a close free-living relative, the cyanobacterium Synechococcus sp. WH 5701. We found that the evolution of free-living to host-restricted lifestyle rendered a fragile metabolic network where >80% of genes in the chromatophore are essential for metabolic functionality. Despite the lack of experimental information, the metabolic reconstruction of the chromatophore suggests that the host provides several metabolites to the endosymbiont. By using these metabolites as intracellular conditions, in silico simulations of genome evolution by gene lose recover with 77% accuracy the actual metabolic gene content of the chromatophore. Also, the metabolic model of the chromatophore allowed us to predict by flux balance analysis a maximum rate of reduced-carbon released by the endosymbiont to the host. By inspecting the central metabolism of the chromatophore and the free-living cyanobacteria we found that by improvements in the gluconeogenic pathway the metabolism of the endosymbiont uses more efficiently the carbon source for reduced-carbon production. In addition, our in silico simulations of the evolutionary process leading to the reduced metabolic network of the chromatophore showed that the predicted rate of released reduced-carbon is obtained in less than 5% of the times under a process guided by random gene deletion and genetic drift. We interpret previous findings as evidence that natural selection at holobiont level shaped the rate at which reduced-carbon is exported to the host. Finally, our model also predicts that the ABC phosphate transporter (pstSACB) which is conserved in the genome of the chromatophore of P. chromatophora strain CCAC 0185 is a necessary component to release reduced-carbon molecules to the host.ConclusionOur evolutionary analysis suggests that in the case of Paulinella chromatophora natural selection at the holobiont level played a prominent role in shaping the metabolic specialization of the chromatophore. We propose that natural selection acted as a “metabolic engineer” by favoring metabolic restructurings that led to an increased release of reduced-carbon to the host.