Journal articles: 'Population genetic models'

1

Pearce, G. P., and H. G. Spencer. "Population genetic models of genomic imprinting." Genetics 130, no. 4 (April 1, 1992): 899–907. http://dx.doi.org/10.1093/genetics/130.4.899.

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Abstract The phenomenon of genomic imprinting has recently excited much interest among experimental biologists. The population genetic consequences of imprinting, however, have remained largely unexplored. Several population genetic models are presented and the following conclusions drawn: (i) systems with genomic imprinting need not behave similarly to otherwise identical systems without imprinting; (ii) nevertheless, many of the models investigated can be shown to be formally equivalent to models without imprinting; (iii) consequently, imprinting often cannot be discovered by following allele frequency changes or examining equilibrium values; (iv) the formal equivalences fail to preserve some well known properties. For example, for populations incorporating genomic imprinting, parameter values exist that cause these populations to behave like populations without imprinting, but with heterozygote advantage, even though no such advantage is present in these imprinting populations. We call this last phenomenon "pseudoheterosis." The imprinting systems that fail to be formally equivalent to nonimprinting systems are those in which males and females are not equivalent, i.e., two-sex viability systems and sex-chromosome inactivation.

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Innan, Hideki. "Population genetic models of duplicated genes." Genetica 137, no. 1 (March 6, 2009): 19–37. http://dx.doi.org/10.1007/s10709-009-9355-1.

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Nagylaki, Thomas. "Multinomial-Sampling Models for Random Genetic Drift." Genetics 145, no. 2 (February 1, 1997): 485–91. http://dx.doi.org/10.1093/genetics/145.2.485.

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Three different derivations of models with multinomial sampling of genotypes in a finite population are presented. The three derivations correspond to the operation of random drift through population regulation, conditioning on the total number of progeny, and culling, respectively. Generations are discrete and nonoverlapping; the diploid population mates at random. Each derivation applies to a single multiallelic locus in a monoecious or dioecious population; in the latter case, the locus may be autosomal or X-linked. Mutation and viability selection are arbitrary; there are no fertility differences. In a monoecious population, the model yields the Wright-Fisher model (i.e., multinomial sampling of genes) if and only if the viabilities are multiplicative. In a dioecious population, the analogous reduction does not occur even for pure random drift. Thus, multinomial sampling of genotypes generally does not lead to multinomial sampling of genes. Although the Wright-Fisher model probably lacks a sound biological basis and may be inaccurate for small populations, it is usually (perhaps always) a good approximation for genotypic multinomial sampling in large populations.

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Fearnhead, Paul. "Perfect Simulation From Nonneutral Population Genetic Models: Variable Population Size and Population Subdivision." Genetics 174, no. 3 (September 1, 2006): 1397–406. http://dx.doi.org/10.1534/genetics.106.060681.

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Gaggiotti, Oscar E. "Population Genetic Models of Source–Sink Metapopulations." Theoretical Population Biology 50, no. 2 (October 1996): 178–208. http://dx.doi.org/10.1006/tpbi.1996.0028.

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Frisman, E. Ya, O. L. Zhdanova, and G. P. Neverova. "Ecological and Genetic Models in Population Biophysics." Biophysics 65, no. 5 (September 2020): 810–25. http://dx.doi.org/10.1134/s0006350920050061.

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Huttley, G. A., and S. R. Wilson. "Testing for Concordant Equilibria Between Population Samples." Genetics 156, no. 4 (December 1, 2000): 2127–35. http://dx.doi.org/10.1093/genetics/156.4.2127.

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Abstract A substantial body of theory has been developed to assess the effect of evolutionary forces on the distribution of genotypes, both single and multilocus, within populations. One area where the potential for application of this theory has not been fully appreciated concerns the extent to which population samples differ. Within populations, the divergence of genotype or haplotype frequencies from that expected under Hardy-Weinberg (HW) or linkage equilibrium can be measured as disequilibria coefficients. To assess population samples for concordant equilibria, an analytical framework for comparing disequilibria coefficients between populations is necessary. Here we present log-linear models to evaluate such hypotheses. These models have broad utility ranging from conventional population genetics to genetic epidemiology. We demonstrate the use of these log-linear models (1) as a test for genetic association with disease and (2) as a test for different levels of linkage disequilibria between human populations.

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Kelly, S. Thomas, and Hamish G. Spencer. "Population-genetic models of sex-limited genomic imprinting." Theoretical Population Biology 115 (June 2017): 35–44. http://dx.doi.org/10.1016/j.tpb.2017.03.004.

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Day, Troy, and Sylvain Gandon. "Applying population-genetic models in theoretical evolutionary epidemiology." Ecology Letters 10, no. 10 (October 2007): 876–88. http://dx.doi.org/10.1111/j.1461-0248.2007.01091.x.

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10

Fearnhead, Paul. "Perfect Simulation from Population Genetic Models with Selection." Theoretical Population Biology 59, no. 4 (June 2001): 263–79. http://dx.doi.org/10.1006/tpbi.2001.1514.

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Maruyama, Takeo, and Paul A. Fuerst. "POPULATION BOTTLENECKS AND NONEQUILIBRIUM MODELS IN POPULATION GENETICS. III. GENIC HOMOZYGOSITY IN POPULATIONS WHICH EXPERIENCE PERIODIC BOTTLENECKS." Genetics 111, no. 3 (November 1, 1985): 691–703. http://dx.doi.org/10.1093/genetics/111.3.691.

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ABSTRACT The amount of variability in a population that experiences repeated restrictions in population size has been calculated. The restrictions in size occur cyclically with a fixed cycle length. Analytical formulas for describing the gene identity at any specific time in the expanded and restricted phases of the cycle, and for the average and second moment of the gene identity, have been derived. It is shown that the level of genetic diversity depends critically on the two parameters that account for the population size, mutation rate and the time of duration for each of the two phases in the cycle. If one or both of these composite parameters are small, the gene diversity will be much reduced, and population gene diversity will then be predictable from knowledge of the harmonic mean population size over the entire cycle. If these parameters take on intermediate values, diversity changes constantly during the cycle, fluctuating steadily from a high to a low value and back again. If these parameters are large, gene diversity will fluctuate rapidly between extreme values and will stay at the extremes for long periods of time.

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Ray, Nicolas, and Laurent Excoffier. "Inferring Past Demography Using Spatially Explicit Population Genetic Models." Human Biology 81, no. 2-3 (April 2009): 141–57. http://dx.doi.org/10.3378/027.081.0303.

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Der, Ricky, Charles L. Epstein, and Joshua B. Plotkin. "Generalized population models and the nature of genetic drift." Theoretical Population Biology 80, no. 2 (September 2011): 80–99. http://dx.doi.org/10.1016/j.tpb.2011.06.004.

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Servedio, Maria R., and Russell Lande. "POPULATION GENETIC MODELS OF MALE AND MUTUAL MATE CHOICE." Evolution 60, no. 4 (2006): 674. http://dx.doi.org/10.1554/05-509.1.

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Servedio, Maria R., and Russell Lande. "POPULATION GENETIC MODELS OF MALE AND MUTUAL MATE CHOICE." Evolution 60, no. 4 (April 2006): 674–85. http://dx.doi.org/10.1111/j.0014-3820.2006.tb01147.x.

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16

Zeng, Z. B., and C. C. Cockerham. "Mutation models and quantitative genetic variation." Genetics 133, no. 3 (March 1, 1993): 729–36. http://dx.doi.org/10.1093/genetics/133.3.729.

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Abstract Analyses of evolution and maintenance of quantitative genetic variation depend on the mutation models assumed. Currently two polygenic mutation models have been used in theoretical analyses. One is the random walk mutation model and the other is the house-of-cards mutation model. Although in the short term the two models give similar results for the evolution of neutral genetic variation within and between populations, the predictions of the changes of the variation are qualitatively different in the long term. In this paper a more general mutation model, called the regression mutation model, is proposed to bridge the gap of the two models. The model regards the regression coefficient, gamma, of the effect of an allele after mutation on the effect of the allele before mutation as a parameter. When gamma = 1 or 0, the model becomes the random walk model or the house-of-cards model, respectively. The additive genetic variances within and between populations are formulated for this mutation model, and some insights are gained by looking at the changes of the genetic variances as gamma changes. The effects of gamma on the statistical test of selection for quantitative characters during macroevolution are also discussed. The results suggest that the random walk mutation model should not be interpreted as a null hypothesis of neutrality for testing against alternative hypotheses of selection during macroevolution because it can potentially allocate too much variation for the change of population means under neutrality.

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Tanaka, Mark M., Romane Cristescu, and Desmond W. Cooper. "Effective population size of koala populations under different population management regimes including contraception." Wildlife Research 36, no. 7 (2009): 601. http://dx.doi.org/10.1071/wr08160.

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Context. The management of wildlife populations aiming to control population size should also consider the preservation of genetic diversity. Some overabundant koala populations, for example, have low genetic variation. Different management strategies will affect population genetic variation differently. Aims. Here, we compare four strategies with respect to their effects on the effective population size, Ne , and therefore on genetic variation. Methods. The four strategies of interest are: (1) sterilisation or culling (which have the same effect on genetic variation); (2) random contraception of females with replacement; (3) random contraception of females without replacement; and (4) regular contraception, giving every female equal opportunity to reproduce. We develop mathematical models of these alternative schemes to evaluate their impact on Ne . We also consider the effect of changing population sizes by investigating a model with geometric population growth in which females are removed by sterilisation or culling. Key results. We find that sterilisation/culling at sexual maturity has the most detrimental effect on Ne , whereas regular contraception has no impact on Ne . Random contraception lies between these two extremes, leading to a moderate reduction in Ne . Removal of females from a growing population results in a higher Ne than the removal of females from a static population. Conclusions. Different strategies for controlling a population lead to different effective population sizes. Implications. To preserve genetic diversity in a wildlife population under control, the effective population size should be kept as large as possible. We suggest that a suitable approach in managing koala populations may be to prevent reproduction by all females older than a particular age.

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ROUZIC, ARNAUD LE, and GRÉGORY DECELIERE. "Models of the population genetics of transposable elements." Genetical Research 85, no. 3 (June 2005): 171–81. http://dx.doi.org/10.1017/s0016672305007585.

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Although transposable elements (TEs) have been found in all organisms in which they have been looked for, the ways in which they invade genomes and populations are still a matter of debate. By extending the classical models of population genetics, several approaches have been developed to account for the dynamics of TEs, especially in Drosophila melanogaster. While the formalism of these models is based on simplifications, they enable us to understand better how TEs invade genomes, as a result of multiple evolutionary forces including duplication, deletion, self-regulation, natural selection and genetic drift. The aim of this paper is to review the assumptions and the predictions of these different models by highlighting the importance of the specific characteristics of both the TEs and the hosts, and the host/TE relationships. Then, perspectives in this domain will be discussed.

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19

Long, J. C. "The genetic structure of admixed populations." Genetics 127, no. 2 (February 1, 1991): 417–28. http://dx.doi.org/10.1093/genetics/127.2.417.

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Abstract A method for simultaneously estimating the admixture proportions of a hybrid population and Wright's fixation index, FST, for that hybrid is presented. It is shown that the variance of admixture estimates can be partitioned into two components: (1) due to sample size, and (2) due to evolutionary variance (i.e., genetic drift). A chi-square test used to detect heterogeneity of admixture estimates from different alleles, or loci, can now be corrected for both sources of random errors. Hence, its value for the detection of natural selection from heterogeneous admixture estimates is improved. The estimation and testing procedures described above are independent of the dynamics of the admixture process. However, when the admixture dynamics can be specified, FST can be predicted from genetic principles. Two admixture models are considered here, gene flow and intermixture. These models are of value because they lead to very different predictions regarding the accumulation of genes from the parental populations and the accumulation of variance due to genetic drift. When there is not evidence for natural selection, and it is appropriate to apply these models to data, the variance effective size (Ne) of the hybrid population can be estimated. Applications are made to three human populations: two of these are Afro-American populations and one is a Yanomamö Indian village. Natural selection could not be detected using the chi-square test in any of these populations. However, estimates of effective population sizes do lead to a richer description of the genetic structure of these populations.

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20

Loog, Liisa. "Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories." Philosophical Transactions of the Royal Society B: Biological Sciences 376, no. 1816 (November 30, 2020): 20190719. http://dx.doi.org/10.1098/rstb.2019.0719.

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Demographic processes directly affect patterns of genetic variation within contemporary populations as well as future generations, allowing for demographic inference from patterns of both present-day and past genetic variation. Advances in laboratory procedures, sequencing and genotyping technologies in the past decades have resulted in massive increases in high-quality genome-wide genetic data from present-day populations and allowed retrieval of genetic data from archaeological material, also known as ancient DNA. This has resulted in an explosion of work exploring past changes in population size, structure, continuity and movement. However, as genetic processes are highly stochastic, patterns of genetic variation only indirectly reflect demographic histories. As a result, past demographic processes need to be reconstructed using an inferential approach. This usually involves comparing observed patterns of variation with model expectations from theoretical population genetics. A large number of approaches have been developed based on different population genetic models that each come with assumptions about the data and underlying demography. In this article I review some of the key models and assumptions underlying the most commonly used approaches for past demographic inference and their consequences for our ability to link the inferred demographic processes to the archaeological and climate records. This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.

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Padhukasahasram, Badri, Paul Marjoram, Jeffrey D. Wall, Carlos D. Bustamante, and Magnus Nordborg. "Exploring Population Genetic Models With Recombination Using Efficient Forward-Time Simulations." Genetics 178, no. 4 (April 2008): 2417–27. http://dx.doi.org/10.1534/genetics.107.085332.

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22

Kaeuffer, Renaud, David W. Coltman, Jean-Louis Chapuis, Dominique Pontier, and Denis Réale. "Unexpected heterozygosity in an island mouflon population founded by a single pair of individuals." Proceedings of the Royal Society B: Biological Sciences 274, no. 1609 (November 28, 2006): 527–33. http://dx.doi.org/10.1098/rspb.2006.3743.

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In population and conservation genetics, there is an overwhelming body of evidence that genetic diversity is lost over time in small populations. This idea has been supported by comparative studies showing that small populations have lower diversity than large populations. However, longitudinal studies reporting a decline in genetic diversity throughout the whole history of a given wild population are much less common. Here, we analysed changes in heterozygosity over time in an insular mouflon ( Ovis aries ) population founded by two individuals in 1957 and located on one of the most isolated locations in the world: the Kerguelen Sub-Antarctic archipelago. Heterozygosity measured using 25 microsatellite markers has actually increased over 46 years since the introduction, and exceeds the range predicted by neutral genetic models and stochastic simulations. Given the complete isolation of the population and the short period of time since the introduction, changes in genetic variation cannot be attributed to mutation or migration. Several lines of evidence suggest that the increase in heterozygosity with time may be attributable to selection. This study shows the importance of longitudinal genetic surveys for understanding the mechanisms that regulate genetic diversity in wild populations.

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Svedberg, Jesper, Vladimir Shchur, Solomon Reinman, Rasmus Nielsen, and Russell Corbett-Detig. "Inferring Adaptive Introgression Using Hidden Markov Models." Molecular Biology and Evolution 38, no. 5 (January 27, 2021): 2152–65. http://dx.doi.org/10.1093/molbev/msab014.

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Abstract Adaptive introgression—the flow of adaptive genetic variation between species or populations—has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a hidden Markov model-based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized data sets for realistic population and selection parameters. We apply Ancestry_HMM-S to a data set of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in data sets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.

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Kelly, John K., Scott Williamson, Maria E. Orive, Marilyn S. Smith, and Robert D. Holt. "Linking Dynamical and Population Genetic Models of Persistent Viral Infection." American Naturalist 162, no. 1 (July 2003): 14–28. http://dx.doi.org/10.1086/375543.

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Jenkins, Paul A. "Stopping-Time Resampling and Population Genetic Inference under Coalescent Models." Statistical Applications in Genetics and Molecular Biology 11, no. 1 (January 6, 2012): 1–20. http://dx.doi.org/10.2202/1544-6115.1770.

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Sul, Jae Hoon, Lana S. Martin, and Eleazar Eskin. "Population structure in genetic studies: Confounding factors and mixed models." PLOS Genetics 14, no. 12 (December 27, 2018): e1007309. http://dx.doi.org/10.1371/journal.pgen.1007309.

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Rousset, François. "Genetic Differentiation and Estimation of Gene Flow from F-Statistics Under Isolation by Distance." Genetics 145, no. 4 (April 1, 1997): 1219–28. http://dx.doi.org/10.1093/genetics/145.4.1219.

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I reexamine the use of isolation by distance models as a basis for the estimation of demographic parameters from measures of population subdivision. To that aim, I first provide results for values of F-statistics in one-dimensional models and coalescence times in two-dimensional models, and make more precise earlier results for F-statistics in two-dimensional models and coalescence times in one-dimensional models. Based on these results, I propose a method of data analysis involving the regression of FST/ (1 – FST) estimates for pairs of subpopulations on geographic distance for populations along linear habitats or logarithm of distance for populations in two-dimensional habitats. This regression provides in principle an estimate of the product of population density and second moment of parental axial distance. In two cases where comparison to direct estimates is possible, the method proposed here is more satisfactory than previous indirect methods.

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Moreira, M. A. M., C. R. Bonvicino, M. A. Soares, and H. N. Seuánez. "Genetic Diversity of Neotropical Primates: Phylogeny, Population Genetics, and Animal Models for Infectious Diseases." Cytogenetic and Genome Research 128, no. 1-3 (2010): 88–98. http://dx.doi.org/10.1159/000291485.

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Battey, C. J., Peter L. Ralph, and Andrew D. Kern. "Space is the Place: Effects of Continuous Spatial Structure on Analysis of Population Genetic Data." Genetics 215, no. 1 (March 24, 2020): 193–214. http://dx.doi.org/10.1534/genetics.120.303143.

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Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright’s neighborhood size is < 100 and sampling is spatially clustered. “Stepping-stone” models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.

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Zhivotovsky, Lev A., A. J. Gharrett, A. J. McGregor, M. K. Glubokovsky, and Marcus W. Feldman. "Gene Differentiation in Pacific Salmon (Oncorhynchus sp.): Facts and Models with Reference to Pink Salmon (O. gorbuscha)." Canadian Journal of Fisheries and Aquatic Sciences 51, S1 (December 19, 1994): 223–32. http://dx.doi.org/10.1139/f94-308.

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Analyzing population genetic data usually involves examining relationships among populations followed by analysis of the distribution of genetic variability. Genetic relationships are often depicted with multidimensional scaling or trees constructed from genetic distances; genetic variation within and among populations is partitioned using gene diversity measures such as FST or GST. Genetic distances or gene diversity are often used to estimate influences of gene drift, migration, and/or selection on observed gene differentiation. We used allozyme data for pink salmon populations to examine the theoretical models available for estimating magnitudes of these factors in Pacific salmon populations. The models included (1) mutation and gene drift; (2) mutation and migration; (3) migration and gene drift; and (4) gene drift, migration, and selection. These models suggest that gene drift and migration are probably important at the lowest levels of population hierarchy, but even very small forces such as weak heterogeneous selection and low migration levels may be important at higher levels. The accuracy of some estimates should be questioned because for many situations appropriate models are either not yet available or are not sufficiently refined. Also, the dynamic genetic structure of salmon populations makes it unlikely that the steady state assumed for many theoretical models has obtained.

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Eldon, Bjarki. "Evolutionary Genomics of High Fecundity." Annual Review of Genetics 54, no. 1 (November 23, 2020): 213–36. http://dx.doi.org/10.1146/annurev-genet-021920-095932.

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Natural highly fecund populations abound. These range from viruses to gadids. Many highly fecund populations are economically important. Highly fecund populations provide an important contrast to the low-fecundity organisms that have traditionally been applied in evolutionary studies. A key question regarding high fecundity is whether large numbers of offspring are produced on a regular basis, by few individuals each time, in a sweepstakes mode of reproduction. Such reproduction characteristics are not incorporated into the classical Wright–Fisher model, the standard reference model of population genetics, or similar types of models, in which each individual can produce only small numbers of offspring relative to the population size. The expected genomic footprints of population genetic models of sweepstakes reproduction are very different from those of the Wright–Fisher model. A key, immediate issue involves identifying the footprints of sweepstakes reproduction in genomic data. Whole-genome sequencing data can be used to distinguish the patterns made by sweepstakes reproduction from the patterns made by population growth in a population evolving according to the Wright–Fisher model (or similar models). If the hypothesis of sweepstakes reproduction cannot be rejected, then models of sweepstakes reproduction and associated multiple-merger coalescents will become at least as relevant as the Wright–Fisher model (or similar models) and the Kingman coalescent, the cornerstones of mathematical population genetics, in further discussions of evolutionary genomics of highly fecund populations.

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Rozenfeld, Alejandro F., Sophie Arnaud-Haond, Emilio Hernández-García, Víctor M. Eguíluz, Manuel A. Matías, Ester Serrão, and Carlos M. Duarte. "Spectrum of genetic diversity and networks of clonal organisms." Journal of The Royal Society Interface 4, no. 17 (May 2007): 1093–102. http://dx.doi.org/10.1098/rsif.2007.0230.

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Clonal reproduction characterizes a wide range of species including clonal plants in terrestrial and aquatic ecosystems, and clonal microbes such as bacteria and parasitic protozoa, with a key role in human health and ecosystem processes. Clonal organisms present a particular challenge in population genetics because, in addition to the possible existence of replicates of the same genotype in a given sample, some of the hypotheses and concepts underlying classical population genetics models are irreconcilable with clonality. The genetic structure and diversity of clonal populations were examined using a combination of new tools to analyse microsatellite data in the marine angiosperm Posidonia oceanica . These tools were based on examination of the frequency distribution of the genetic distance among ramets, termed the spectrum of genetic diversity (GDS), and of networks built on the basis of pairwise genetic distances among genets. Clonal growth and outcrossing are apparently dominant processes, whereas selfing and somatic mutations appear to be marginal, and the contribution of immigration seems to play a small role in adding genetic diversity to populations. The properties and topology of networks based on genetic distances showed a ‘small-world’ topology, characterized by a high degree of connectivity among nodes, and a substantial amount of substructure, revealing organization in subfamilies of closely related individuals. The combination of GDS and network tools proposed here helped in dissecting the influence of various evolutionary processes in shaping the intra-population genetic structure of the clonal organism investigated; these therefore represent promising analytical tools in population genetics.

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Richards, Martin. "The Neolithic transition in Europe: archaeological models and genetic evidence." Documenta Praehistorica 30 (January 1, 2003): 159–67. http://dx.doi.org/10.4312/dp.30.10.

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The major pattern in the European gene pool is a southeast-northwest frequency gradient of classic genetic markers such as blood groups, which population geneticists initially attributed to the demographic impact of Neolithic farmers dispersing from the Near East. Molecular genetics has enriched this picture, with analyses of mitochondrial DNA and the Y chromosome allowing a more detailed exploration of alternative models for the spread of the Neolithic into Europe. This paper considers a range of possible models in the light of the detailed information now emerging from genetic studies.

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Rehfeldt, Gerald E. "Adaptation of Picea engelmannii populations to the heterogeneous environments of the Intermountain West." Canadian Journal of Botany 72, no. 8 (August 1, 1994): 1197–208. http://dx.doi.org/10.1139/b94-146.

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Seedlings from 104 natural populations of Engelmann spruce (Picea engelmannii) and 10 blue spruce (Picea pungens) populations from the Intermountain West, U.S.A., were compared in common gardens. Comparisons involved 16 characters that described growth, development, and cold hardiness plus nine monoterpenes. Canonical discriminant analyses detected one population of blue spruce that had been misidentified, readily separated populations of blue and Engelmann spruce, suggested that three Southwest populations differed markedly from Intermountain populations of Engelmann spruce, but identified no Intermountain populations that reflected introgression with blue spruce. Genetic differences were detected among populations of Engelmann spruce for 16 of the morphometric characters, and multiple regression models accounted for as much as 70% of the variance among populations. The regressions described genetic variation occurring along clines that were dominated by elevational and latitudinal effects. The slope of the clines, however, was relatively gentle; populations located within the same physiographic province must be separated by at least 420 m in elevation before genetic differentiation becomes a reasonable possibility. By providing a means for assessing the degree by which similar genotypes recur across the landscape, the regression models have direct practical application in programs ranging from land management to conservation biology. Key words: population differentiation, genetic variation, ecological genetics.

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Mimno, David, David M. Blei, and Barbara E. Engelhardt. "Posterior predictive checks to quantify lack-of-fit in admixture models of latent population structure." Proceedings of the National Academy of Sciences 112, no. 26 (June 12, 2015): E3441—E3450. http://dx.doi.org/10.1073/pnas.1412301112.

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Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies.

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GILLOIS, MICHEL. "GENETIC INTERPRETATION OF DISCRETE HEREDITY I: FINITE SET THEORY ORDERS GENES IN SMALL POPULATION." Journal of Biological Systems 03, no. 04 (December 1995): 1141–55. http://dx.doi.org/10.1142/s0218339095001039.

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E. Mayr [55] emphasizes that population genetic theories regard a population as a bag full of colored beans. Such a simplified way of thinking is misleading. M. Gillois [19,20] introduces finite set theory in population genetic theories. Consequently he orders genes in small population and he develops new concepts as "identity situations", "constraint situations" and "generalized genotypes". This paper presents these new concepts which shall be used in order to study dynamics of genes in small populations. These results are basic for deterministic models. Contrary to stochastic models, deterministic models are fully in accordance to the physical fate of genes through individual meiosis and mating.

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Vose, Michael D. "Modeling Simple Genetic Algorithms." Evolutionary Computation 3, no. 4 (December 1995): 453–72. http://dx.doi.org/10.1162/evco.1995.3.4.453.

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The infinite- and finite-population models of the simple genetic algorithm are extended and unified, The result incorporates both transient and asymptotic GA behavior. This leads to an interpretation of genetic search that partially explains population trajectories. In particular, the asymptotic behavior of the large-population simple genetic algorithm is analyzed.

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Schubert, Ryan, Angela Andaleon, and Heather E. Wheeler. "Comparing local ancestry inference models in populations of two- and three-way admixture." PeerJ 8 (October 2, 2020): e10090. http://dx.doi.org/10.7717/peerj.10090.

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Local ancestry estimation infers the regional ancestral origin of chromosomal segments in admixed populations using reference populations and a variety of statistical models. Integrating local ancestry into complex trait genetics has the potential to increase detection of genetic associations and improve genetic prediction models in understudied admixed populations, including African Americans and Hispanics. Five methods for local ancestry estimation that have been used in human complex trait genetics are LAMP-LD (2012), RFMix (2013), ELAI (2014), Loter (2018), and MOSAIC (2019). As users rather than developers, we sought to perform direct comparisons of accuracy, runtime, memory usage, and usability of these software tools to determine which is best for incorporation into association study pipelines. We find that in the majority of cases RFMix has the highest median accuracy with the ranking of the remaining software dependent on the ancestral architecture of the population tested. Additionally, we estimate the O(n) of both memory and runtime for each software and find that for both time and memory most software increase linearly with respect to sample size. The only exception is RFMix, which increases quadratically with respect to runtime and linearly with respect to memory. Effective local ancestry estimation tools are necessary to increase diversity and prevent population disparities in human genetics studies. RFMix performs the best across methods, however, depending on application, other methods perform just as well with the benefit of shorter runtimes. Scripts used to format data, run software, and estimate accuracy can be found at https://github.com/WheelerLab/LAI_benchmarking.

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D’Aloia, Cassidy C., Christina B. Azodi, Sallie P. Sheldon, Stephen C. Trombulak, and William R. Ardren. "Genetic models reveal historical patterns of sea lamprey population fluctuations within Lake Champlain." PeerJ 3 (October 29, 2015): e1369. http://dx.doi.org/10.7717/peerj.1369.

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The origin of sea lamprey (Petromyzon marinus) in Lake Champlain has been heavily debated over the past decade. Given the lack of historical documentation, two competing hypotheses have emerged in the literature. First, it has been argued that the relatively recent population size increase and concomitant rise in wounding rates on prey populations are indicative of an invasive population that entered the lake through the Champlain Canal. Second, recent genetic evidence suggests a post-glacial colonization at the end of the Pleistocene, approximately 11,000 years ago. One limitation to resolving the origin of sea lamprey in Lake Champlain is a lack of historical and current measures of population size. In this study, the issue of population size was explicitly addressed using nuclear (nDNA) and mitochondrial DNA (mtDNA) markers to estimate historical demography with genetic models. Haplotype network analysis, mismatch analysis, and summary statistics based on mtDNA noncoding sequences for NCI (479 bp) and NCII (173 bp) all indicate a recent population expansion. Coalescent models based on mtDNA and nDNA identified two potential demographic events: a population decline followed by a very recent population expansion. The decline in effective population size may correlate with land-use and fishing pressure changes post-European settlement, while the recent expansion may be associated with the implementation of the salmonid stocking program in the 1970s. These results are most consistent with the hypothesis that sea lamprey are native to Lake Champlain; however, the credibility intervals around parameter estimates demonstrate that there is uncertainty regarding the magnitude and timing of past demographic events.

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Janko, Karel, Pavel Drozd, and Jan Eisner. "Do clones degenerate over time? Explaining the genetic variability of asexuals through population genetic models." Biology Direct 6, no. 1 (2011): 17. http://dx.doi.org/10.1186/1745-6150-6-17.

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Buzbas, Erkan O., and Noah A. Rosenberg. "AABC: Approximate approximate Bayesian computation for inference in population-genetic models." Theoretical Population Biology 99 (February 2015): 31–42. http://dx.doi.org/10.1016/j.tpb.2014.09.002.

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Joshi, N. V. "Sibling rivalry between seeds within a fruit: Some population genetic models." Journal of Genetics 71, no. 3 (December 1992): 105–19. http://dx.doi.org/10.1007/bf02927891.

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Elketroussi, Mehdi, and David P. Fan. "Optimization of simulation models with GADELO: a multi-population genetic algorithm." International Journal of Bio-Medical Computing 35, no. 1 (February 1994): 61–77. http://dx.doi.org/10.1016/0020-7101(94)90049-3.

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Maruyama, Takeo, and Paul A. Fuerst. "POPULATION BOTTLENECKS AND NONEQUILIBRIUM MODELS IN POPULATION GENETICS. II. NUMBER OF ALLELES IN A SMALL POPULATION THAT WAS FORMED BY A RECENT BOTTLENECK." Genetics 111, no. 3 (November 1, 1985): 675–89. http://dx.doi.org/10.1093/genetics/111.3.675.

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ABSTRACT A model is presented in which a large population in mutation/drift equilibrium undergoes a severe restriction in size and subsequently remains at the small size. The rate of loss of genetic variability has been studied. Allelic loss occurs more rapidly than loss of genic heterozygosity. Rare alleles are lost especially rapidly. The result is a transient deficiency in the total number of alleles observed in samples taken from the reduced population when compared with the number expected in a sample from a steady-state population having the same observed heterozygosity. Alternatively, the population can be considered to posses excess gene diversity if the number of alleles is used as the statistical estimator of mutation rate. The deficit in allele number arises principally from a lack of those alleles that are expected to appear only once or twice in the sample. The magnitude of the allelic deficiency is less, however, than the excess that an earlier study predicted to follow a rapid population expansion. This suggests that populations that have undergone a single bottleneck event, followed by rapid population growth, should have an apparent excess number of alleles, given the observed level of genic heterozygosity and provided that the bottleneck has not occurred very recently. Conversely, such populations will be deficient for observed heterozygosity if allele number is used as the sufficient statistic for the estimation of 4Nev. Populations that have undergone very recent restrictions in size should show the opposite tendencies.

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Ghosh, Atiyo, Patrick G. Meirmans, and Patsy Haccou. "Quantifying introgression risk with realistic population genetics." Proceedings of the Royal Society B: Biological Sciences 279, no. 1748 (October 10, 2012): 4747–54. http://dx.doi.org/10.1098/rspb.2012.1907.

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Introgression is the permanent incorporation of genes from the genome of one population into another. This can have severe consequences, such as extinction of endemic species, or the spread of transgenes. Quantification of the risk of introgression is an important component of genetically modified crop regulation. Most theoretical introgression studies aimed at such quantification disregard one or more of the most important factors concerning introgression: realistic genetical mechanisms, repeated invasions and stochasticity. In addition, the use of linkage as a risk mitigation strategy has not been studied properly yet with genetic introgression models. Current genetic introgression studies fail to take repeated invasions and demographic stochasticity into account properly, and use incorrect measures of introgression risk that can be manipulated by arbitrary choices. In this study, we present proper methods for risk quantification that overcome these difficulties. We generalize a probabilistic risk measure, the so-called hazard rate of introgression, for application to introgression models with complex genetics and small natural population sizes. We illustrate the method by studying the effects of linkage and recombination on transgene introgression risk at different population sizes.

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Geza, Ephifania, Jacquiline Mugo, Nicola J. Mulder, Ambroise Wonkam, Emile R. Chimusa, and Gaston K. Mazandu. "A comprehensive survey of models for dissecting local ancestry deconvolution in human genome." Briefings in Bioinformatics 20, no. 5 (June 29, 2018): 1709–24. http://dx.doi.org/10.1093/bib/bby044.

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Abstract Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.

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JARNE, P., and A. THÉRON. "Genetic structure in natural populations of flukes and snails: a practical approach and review." Parasitology 123, no. 7 (November 2001): 27–40. http://dx.doi.org/10.1017/s0031182001007715.

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Several aspects of the coevolutionary dynamics in host-parasite systems may be better quantified based on analyses of population structure using neutral genetic markers. This includes, for example, the migration rates of hosts and parasites. In this respect, the current situation, especially in fluke-snail systems is unsatisfactory, since basic population genetics data are lacking and the appropriate methodology has rarely been used. After reviewing the forces acting on population structure (e.g. genetic drift or the mating system) and how they can be analysed in models of structured populations, we propose a simplified, indicative framework for conducting analyses of population structure in hosts and parasites. This includes consideration of markers, sampling, data analysis, comparison of structure in hosts and parasites and use of external data (e.g. from population dynamics). We then focus on flukes and snails, highlighting important biological traits with regard to population structure. The few available studies indicate that asexual amplification of flukes within snails strongly influences adult flukes populations. They also show that the genetic structure among populations in strongly affected by traits in other than snails (e.g. definitive host dispersal behaviour), as snails populations have limited migration. Finally more studies would allow us to deepen our current understanding of selective interference between flukes and snails (e.g. manipulation of host mating system by parasites), and evaluate how this affect population structure at neutral markers.

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Takahiro Miyo. "Some considerations on care of the elderly, using evolutionary genetic models." World Journal of Advanced Research and Reviews 8, no. 2 (November 30, 2020): 189–202. http://dx.doi.org/10.30574/wjarr.2020.5.2.0414.

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Some evolutionary genetic models that assume pleiotropic constraints among care for old parents and care for infants are developed, in order to examine the evolution of care for the elderly within a population, in which population aging coupled with a tendency toward a decrease in population size is in progress. Not only does this study suggest that high levels of care for old parents could evolve within the population if the cost of care of the elderly is not too heavy, but it also suggests that, if younger generations experience a high cost of elderly care, this behavior might be eliminated from the population, resulting in the loss of high levels of care for infants. It is also suggested that the benefit of the help from the elderly is essential, not only for the behavior of care for old parents to be maintained within the population, but also for population growth, even though there may be a high cost of elderly care. Based on the results obtained, some social issues that some countries, such as Japan, are now, or will be, faced with are discussed.

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Takahiro Miyo. "Some considerations on care of the elderly, using evolutionary genetic models." World Journal of Advanced Research and Reviews 8, no. 2 (November 30, 2020): 189–202. http://dx.doi.org/10.30574/wjarr.2020.8.2.0414.

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Some evolutionary genetic models that assume pleiotropic constraints among care for old parents and care for infants are developed, in order to examine the evolution of care for the elderly within a population, in which population aging coupled with a tendency toward a decrease in population size is in progress. Not only does this study suggest that high levels of care for old parents could evolve within the population if the cost of care of the elderly is not too heavy, but it also suggests that, if younger generations experience a high cost of elderly care, this behavior might be eliminated from the population, resulting in the loss of high levels of care for infants. It is also suggested that the benefit of the help from the elderly is essential, not only for the behavior of care for old parents to be maintained within the population, but also for population growth, even though there may be a high cost of elderly care. Based on the results obtained, some social issues that some countries, such as Japan, are now, or will be, faced with are discussed.

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Baltazar-Soares, Miguel, Hans-Harald Hinrichsen, and Christophe Eizaguirre. "Integrating population genomics and biophysical models towards evolutionary-based fisheries management." ICES Journal of Marine Science 75, no. 4 (January 6, 2018): 1245–57. http://dx.doi.org/10.1093/icesjms/fsx244.

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Abstract Overfishing and rapid environmental shifts pose severe challenges to the resilience and viability of marine fish populations. To develop and implement measures that enhance species’ adaptive potential to cope with those pressures while, at the same time, ensuring sustainable exploitation rates is part of the central goal of fisheries management. Here, we argue that a combination of biophysical modelling and population genomic assessments offer ideal management tools to define stocks, their physical connectivity and ultimately, their short-term adaptive potential. To date, biophysical modelling has often been confined to fisheries ecology whereas evolutionary hypotheses remain rarely considered. When identified, connectivity patterns are seldom explored to understand the evolution and distribution of adaptive genetic variation, a proxy for species’ evolutionary potential. Here, we describe a framework that expands on the conventional seascape genetics approach by using biophysical modelling and population genomics. The goals are to identify connectivity patterns and selective pressures, as well as putative adaptive variants directly responding to the selective pressures and, ultimately, link both to define testable hypotheses over species response to shifting ecological conditions and overexploitation.

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Journal articles on the topic 'Population genetic models'

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