954 resultados para Models, Genetic
Resumo:
We investigated sex-specific recombination rates in Hyla arborea, a species with nascent sex chromosomes and male heterogamety. Twenty microsatellites were clustered into six linkage groups, all showing suppressed or very low recombination in males. Seven markers were sex linked, none of them showing any sign of recombination in males (r=0.00 versus 0.43 on average in females). This opposes classical models of sex chromosome evolution, which envision an initially small differential segment that progressively expands as structural changes accumulate on the Y chromosome. For autosomes, maps were more than 14 times longer in females than in males, which seems the highest ratio documented so far in vertebrates. These results support the pleiotropic model of Haldane and Huxley, according to which recombination is reduced in the heterogametic sex by general modifiers that affect recombination on the whole genome.
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Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
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To study the structure of partially replicated plasmids, we cloned the Escherichia coli polar replication terminator TerE in its active orientation at different locations in the ColE1 vector pBR18. The resulting plasmids, pBR18-TerE@StyI and pBR18-TerE@EcoRI, were analyzed by neutral/neutral two-dimensional agarose gel electrophoresis and electron microscopy. Replication forks stop at the Ter-TUS complex, leading to the accumulation of specific replication intermediates with a mass 1.26 times the mass of non-replicating plasmids for pBR18-TerE@StyI and 1.57 times for pBR18-TerE@EcoRI. The number of knotted bubbles detected after digestion with ScaI and the number and electrophoretic mobility of undigested partially replicated topoisomers reflect the changes in plasmid topology that occur in DNA molecules replicated to different extents. Exposure to increasing concentrations of chloroquine or ethidium bromide revealed that partially replicated topoisomers (CCCRIs) do not sustain positive supercoiling as efficiently as their non-replicating counterparts. It was suggested that this occurs because in partially replicated plasmids a positive DeltaLk is absorbed by regression of the replication fork. Indeed, we showed by electron microscopy that, at least in the presence of chloroquine, some of the CCCRIs of pBR18-Ter@StyI formed Holliday-like junction structures characteristic of reversed forks. However, not all the positive supercoiling was absorbed by fork reversal in the presence of high concentrations of ethidium bromide.
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The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.
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Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co-operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.
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Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.
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Ripglut1;glut2-/- mice have no endogenous glucose transporter type 2 (glut2) gene expression but rescue glucose-regulated insulin secretion. Control of glucagon plasma levels is, however, abnormal, with fed hyperglucagonemia and insensitivity to physiological hypo- or hyperglycemia, indicating that GLUT2-dependent sensors control glucagon secretion. Here, we evaluated whether these sensors were located centrally and whether GLUT2 was expressed in glial cells or in neurons. We showed that ripglut1;glut2-/- mice failed to increase plasma glucagon levels following glucoprivation induced either by i.p. or intracerebroventricular 2-deoxy-D-glucose injections. This was accompanied by failure of 2-deoxy-D-glucose injections to activate c-Fos-like immunoreactivity in the nucleus of the tractus solitarius and the dorsal motor nucleus of the vagus. When glut2 was expressed by transgenesis in glial cells but not in neurons of ripglut1;glut2-/- mice, stimulated glucagon secretion was restored as was c-Fos-like immunoreactive labeling in the brainstem. When ripglut1;glut2-/- mice were backcrossed into the C57BL/6 genetic background, fed plasma glucagon levels were also elevated due to abnormal autonomic input to the alpha cells; glucagon secretion was, however, stimulated by hypoglycemic stimuli to levels similar to those in control mice. These studies identify the existence of central glucose sensors requiring glut2 expression in glial cells and therefore functional coupling between glial cells and neurons. These sensors may be activated at different glycemic levels depending on the genetic background.
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Many traits and/or strategies expressed by organisms are quantitative phenotypes. Because populations are of finite size and genomes are subject to mutations, these continuously varying phenotypes are under the joint pressure of mutation, natural selection and random genetic drift. This article derives the stationary distribution for such a phenotype under a mutation-selection-drift balance in a class-structured population allowing for demographically varying class sizes and/or changing environmental conditions. The salient feature of the stationary distribution is that it can be entirely characterized in terms of the average size of the gene pool and Hamilton's inclusive fitness effect. The exploration of the phenotypic space varies exponentially with the cumulative inclusive fitness effect over state space, which determines an adaptive landscape. The peaks of the landscapes are those phenotypes that are candidate evolutionary stable strategies and can be determined by standard phenotypic selection gradient methods (e.g. evolutionary game theory, kin selection theory, adaptive dynamics). The curvature of the stationary distribution provides a measure of the stability by convergence of candidate evolutionary stable strategies, and it is evaluated explicitly for two biological scenarios: first, a coordination game, which illustrates that, for a multipeaked adaptive landscape, stochastically stable strategies can be singled out by letting the size of the gene pool grow large; second, a sex-allocation game for diploids and haplo-diploids, which suggests that the equilibrium sex ratio follows a Beta distribution with parameters depending on the features of the genetic system.
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In recent years there has been growing interest in the question of how the particular topology of polymeric chains affects their overall dimensions and physical behavior. The majority of relevant studies are based on numerical simulation methods or analytical treatment; however, both these approaches depend on various assumptions and simplifications. Experimental verification is clearly needed but was hampered by practical difficulties in obtaining preparative amounts of knotted or catenated polymers with predefined topology and precisely set chain length. We introduce here an efficient method of production of various single-stranded DNA knots and catenanes that have the same global chain length. We also characterize electrophoretic migration of the produced single-stranded DNA knots and catenanes with increasing complexity.
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Gene copies that stem from the mRNAs of parental source genes have long been viewed as evolutionary dead-ends with little biological relevance. Here we review a range of recent studies that have unveiled a significant number of functional retroposed gene copies in both mammalian and some non-mammalian genomes. These studies have not only revealed previously unknown mechanisms for the emergence of new genes and their functions but have also provided fascinating general insights into molecular and evolutionary processes that have shaped genomes. For example, analyses of chromosomal gene movement patterns via RNA-based gene duplication have shed fresh light on the evolutionary origin and biology of our sex chromosomes.
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To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.
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In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous article presented a histogram model [1] consisting in populations of individuals whose number changed under the influence of variation and/or fitness, the total population remaining constant. Individuals are classified into bins, and the content of each bin is calculated generation after generation by an Excel spreadsheet. Here, we apply the histogram model to a stable population with fitness F(1)=1.00 in which one or two fitter mutants emerge. In a first scenario, a single mutant emerged in the population whose fitness was greater than 1.00. The simulations ended when the original population was reduced to a single individual. The histogram model was validated by excellent agreement between its predictions and those of a classical continuous function (Eqn. 1) which predicts the number of generations needed for a favorable mutation to spread throughout a population. But in contrast to Eqn. 1, our histogram model is adaptable to more complex scenarios, as demonstrated here. In the second and third scenarios, the original population was present at time zero together with two mutants which differed from the original population by two higher and distinct fitness values. In the fourth scenario, the large original population was present at time zero together with one fitter mutant. After a number of generations, when the mutant offspring had multiplied, a second mutant was introduced whose fitness was even greater. The histogram model also allows Shannon entropy (SE) to be monitored continuously as the information content of the total population decreases or increases. The results of these simulations illustrate, in a graphically didactic manner, the influence of natural selection, operating through relative fitness, in the emergence and dominance of a fitter mutant.
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Speciation is a fundamental evolutionary process, the knowledge of which is crucial for understanding the origins of biodiversity. Genomic approaches are an increasingly important aspect of this research field. We review current understanding of genome-wide effects of accumulating reproductive isolation and of genomic properties that influence the process of speciation. Building on this work, we identify emergent trends and gaps in our understanding, propose new approaches to more fully integrate genomics into speciation research, translate speciation theory into hypotheses that are testable using genomic tools and provide an integrative definition of the field of speciation genomics.