953 resultados para Genetics, Population


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The thesis contains the results of an investigation on the " Population Genetic Structure of the Penaeus indicus " from southeast and southwest coasts of India. The P.indicus, popularly known as the Indian white prawn, is distributed widely in the Indo-Pacific, starting from New South wales in Australia in the east to the east coast of Africa in the west. Its heavy demand in the export market, the species has been exploited intensively from all along its areas of distribution in Indian waters. The population genetic characteristics of the species were examined by three independent but complementary techniques, namely, morphometrics (truss network), biochemical genetics (isozyme electrophoresis ) and molecular genetics (RFLP and RAPD). The east and west coast populations of the species may be genetically different. Due to certain constraints, the results obtained from the studies of restriction fragment length 70 polymorphism (RFLP) were limited. The significant difference in the number of bands in the sample populations strongly suggests that these two populations have considerably different population genetic structures

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The objective of present investigation was to study the population genetic structure of S. longiceps by applying three different basic population genetic techniques such as cytogenetics, non-enzymatic biochemicalgenetics (general protein) and morphomeristics/metrics.

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Background Plasmodium vivax is one of the five species causing malaria in human beings, affecting around 391 million people annually. The development of an anti-malarial vaccine has been proposed as an alternative for controlling this disease. However, its development has been hampered by allele-specific responses produced by the high genetic diversity shown by some parasite antigens. Evaluating these antigens’ genetic diversity is thus essential when designing a completely effective vaccine. Methods The gene sequences of Plasmodium vivax p12 (pv12) and p38 (pv38), obtained from field isolates in Colombia, were used for evaluating haplotype polymorphism and distribution by population genetics analysis. The evolutionary forces generating the variation pattern so observed were also determined. Results Both pv12 and pv38 were shown to have low genetic diversity. The neutral model for pv12 could not be discarded, whilst polymorphism in pv38 was maintained by balanced selection restricted to the gene’s 5′ region. Both encoded proteins seemed to have functional/structural constraints due to the presence of s48/45 domains, which were seen to be highly conserved.

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There is great interest in using amplified fragment length polymorphism (AFLP) markers because they are inexpensive and easy to produce. It is, therefore, possible to generate a large number of markers that have a wide coverage of species genotnes. Several statistical methods have been proposed to study the genetic structure using AFLP's but they assume Hardy-Weinberg equilibrium and do not estimate the inbreeding coefficient, F-IS. A Bayesian method has been proposed by Holsinger and colleagues that relaxes these simplifying assumptions but we have identified two sources of bias that can influence estimates based on these markers: (i) the use of a uniform prior on ancestral allele frequencies and (ii) the ascertainment bias of AFLP markers. We present a new Bayesian method that avoids these biases by using an implementation based on the approximate Bayesian computation (ABC) algorithm. This new method estimates population-specific F-IS and F-ST values and offers users the possibility of taking into account the criteria for selecting the markers that are used in the analyses. The software is available at our web site (http://www-leca.uif-grenoble.fi-/logiciels.htm). Finally, we provide advice on how to avoid the effects of ascertainment bias.

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An example of the evolution of the interacting behaviours of parents and progeny is studied using iterative equations linking the frequencies of the gametes produced by the progeny to the frequencies of the gametes in the parental generation. This population genetics approach shows that a model in which both behaviours are determined by a single locus can lead to a stable equilibrium in which the two behaviours continue to segregate. A model in which the behaviours are determined by genes at two separate loci leads eventually to fixation of the alleles at both loci but this can take many generations of selection. Models of the type described in this paper will be needed to understand the evolution of complex behaviour when genomic or experimental information is available about the genetic determinants of behaviour and the selective values of different genomes. (c) 2007 Elsevier Inc. All rights reserved.

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Long distance dispersal (LDD) plays an important role in many population processes like colonization, range expansion, and epidemics. LDD of small particles like fungal spores is often a result of turbulent wind dispersal and is best described by functions with power-law behavior in the tails ("fat tailed"). The influence of fat-tailed LDD on population genetic structure is reported in this article. In computer simulations, the population structure generated by power-law dispersal with exponents in the range of -2 to -1, in distinct contrast to that generated by exponential dispersal, has a fractal structure. As the power-law exponent becomes smaller, the distribution of individual genotypes becomes more self-similar at different scales. Common statistics like G(ST) are not well suited to summarizing differences between the population genetic structures. Instead, fractal and self-similarity statistics demonstrated differences in structure arising from fat-tailed and exponential dispersal. When dispersal is fat tailed, a log-log plot of the Simpson index against distance between subpopulations has an approximately constant gradient over a large range of spatial scales. The fractal dimension D-2 is linearly inversely related to the power-law exponent, with a slope of similar to -2. In a large simulation arena, fat-tailed LDD allows colonization of the entire space by all genotypes whereas exponentially bounded dispersal eventually confines all descendants of a single clonal lineage to a relatively small area.

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We describe and evaluate a new estimator of the effective population size (N-e), a critical parameter in evolutionary and conservation biology. This new "SummStat" N-e. estimator is based upon the use of summary statistics in an approximate Bayesian computation framework to infer N-e. Simulations of a Wright-Fisher population with known N-e show that the SummStat estimator is useful across a realistic range of individuals and loci sampled, generations between samples, and N-e values. We also address the paucity of information about the relative performance of N-e estimators by comparing the SUMMStat estimator to two recently developed likelihood-based estimators and a traditional moment-based estimator. The SummStat estimator is the least biased of the four estimators compared. In 32 of 36 parameter combinations investigated rising initial allele frequencies drawn from a Dirichlet distribution, it has the lowest bias. The relative mean square error (RMSE) of the SummStat estimator was generally intermediate to the others. All of the estimators had RMSE > 1 when small samples (n = 20, five loci) were collected a generation apart. In contrast, when samples were separated by three or more generations and Ne less than or equal to 50, the SummStat and likelihood-based estimators all had greatly reduced RMSE. Under the conditions simulated, SummStat confidence intervals were more conservative than the likelihood-based estimators and more likely to include true N-e. The greatest strength of the SummStat estimator is its flexible structure. This flexibility allows it to incorporate any, potentially informative summary statistic from Population genetic data.

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This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.

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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 Theta to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of Theta, 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.

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A wild house mouse (Mus domesticus) population originally trapped near Reading, Berkshire, United Kingdom, and maintained as a colony in the laboratory, was subjected to the discriminating feeding period of the warfarin resistance test, as used by Wallace and MacSwiney (1976) and derived from the work of Rowe and Redfern (1964). Eighty percent of this heterogeneous population survived the resistance-test. A similar proportion of the population was found to survive the normally lethal dose of bromadiolone administered by oral gavage. The majority of this population of mice were classified as "warfarin-resistant" and "bromadiolone-resistant." The dose of 10mg.kg-1 of bromadiolone administered by oral gavage appeared to give good discrimination between susceptible and resistant individuals. The results of breeding tests indicate a single dominant gene that confers both "warfarin-resistance" and "bromadiolone-resistance", with complete expression of the resistance genotype in both males and females. Individual mice were classified as to genotype by back-crossing to a homozygous-susceptible strain, and resistance-testing the F1 generation. Separate strains of homozygous-resistant and homozygous-susceptible house mice are now being established.

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Genes play an important role in the development of diabetes mellitus. Putative susceptibility genes could be the key to the development of diabetes. Type 1 diabetes mellitus is one of the most common chronic diseases of childhood. A combination of genetic and environmental factors is most likely the cause of Type 1 diabetes. The pathogenetic sequence leading to the selective autoimmune destruction of islet beta-cells and development of Type 1 diabetes involves genetic factors, environmental factors, immune regulation and chemical mediators. Unlike Type 1 diabetes mellitus, Type 2 diabetes is often considered a polygenic disorder with multiple genes located on different chromosomes being associated with this condition. This is further complicated by numerous environmental factors which also contribute to the clinical manifestation of the disorder in genetically predisposed persons. Only a minority of cases of type 2 diabetes are caused by single gene defects such as maturity onset diabetes of the young (MODY), syndrome of insulin resistance (insulin receptor defect) and maternally inherited diabetes and deafness (mitochondrial gene defect). Although Type 2 diabetes mellitus appears in almost epidemic proportions our knowledge of the mechanism of this disease is limited. More information about insulin secretion and action and the genetic variability of the various factors involved will contribute to better understanding and classification of this group of diseases. This article discusses the results of various genetic studies on diabetes with special reference to Indian population.

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MAGIC populations represent one of a new generation of crop genetic mapping resources combining high genetic recombination and diversity. We describe the creation and validation of an eight-parent MAGIC population consisting of 1091 F7 lines of winter-sown wheat (Triticum aestivum L.). Analyses based on genotypes from a 90,000-single nucleotide polymorphism (SNP) array find the population to be well-suited as a platform for fine-mapping quantitative trait loci (QTL) and gene isolation. Patterns of linkage disequilibrium (LD) show the population to be highly recombined; genetic marker diversity among the founders was 74% of that captured in a larger set of 64 wheat varieties, and 54% of SNPs segregating among the 64 lines also segregated among the eight founder lines. In contrast, a commonly used reference bi-parental population had only 54% of the diversity of the 64 varieties with 27% of SNPs segregating. We demonstrate the potential of this MAGIC resource by identifying a highly diagnostic marker for the morphological character "awn presence/absence" and independently validate it in an association-mapping panel. These analyses show this large, diverse, and highly recombined MAGIC population to be a powerful resource for the genetic dissection of target traits in wheat, and it is well-placed to efficiently exploit ongoing advances in phenomics and genomics. Genetic marker and trait data, together with instructions for access to seed, are available at http://www.niab.com/MAGIC/.

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Siderastrea stellata and S. radians are scleractinian coral species that present a remarkable overlap of diagnostic characteristics and sympatric distribution. Moreover, both are viviparous with similar reproductive strategies and with a gregarious larval behavior. Samples of both species from the Brazilian coast were analyzed using 18 isozymic loci to quantify their genetic variability and populational structure. Results confirmed species identity, high intrapopulational variability and revealed moderate genetic structuring among all samples (S. stellata: F(ST) = 0.070; S. radians: F(ST) = 0.092). Based on genotypic diversity analysis, there was evidence that local recruitment may have a minor role in the populations (mean, G(o) :G(e) = 1.00 +/- 0.0003 SD for S. stellata and 0.99 +/- 0.0023 SD for S. radians). Deviations towards heterozygote deficiencies found in both Siderastrea species could be explained by the Wahlund effect, since there was evidence that populations might be composed of colonies of different ages. In S. radians it is also likely that there is some inbreeding occurring in the studied populations. Despite the brooding pattern and the gregarious larval behavior, our data suggest the occurrence of gene flow along the Brazilian coast. This is the first study on population genetics of Brazilian reef corals.