38 resultados para Biological Evolution


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Animal color pattern phenotypes evolve rapidly. What influences their evolution? Because color patterns are used in communication, selection for signal efficacy, relative to the intended receiver's visual system, may explain and predict the direction of evolution. We investigated this in bowerbirds, whose color patterns consist of plumage, bower structure, and ornaments and whose visual displays are presented under predictable visual conditions. We used data on avian vision, environmental conditions, color pattern properties, and an estimate of the bowerbird phylogeny to test hypotheses about evolutionary effects of visual processing. Different components of the color pattern evolve differently. Plumage sexual dimorphism increased and then decreased, while overall (plumage plus bower) visual contrast increased. The use of bowers allows relative crypsis of the bird but increased efficacy of the signal as a whole. Ornaments do not elaborate existing plumage features but instead are innovations (new color schemes) that increase signal efficacy. Isolation between species could be facilitated by plumage but not ornaments, because we observed character displacement only in plumage. Bowerbird color pattern evolution is at least partially predictable from the function of the visual system and from knowledge of different functions of different components of the color patterns. This provides clues to how more constrained visual signaling systems may evolve.

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Many models have been advanced to suggest how different expressions of sociality have evolved and are maintained. However these models ignore the function of groups for the particular species in question. Here we present a new perspective on sociality where the function of the group takes a central role. We argue that sociality may have primarily a reproductive, protective, or foraging function, depending on whether it enhances the reproductive, protective or foraging aspect of the animal's life (sociality may serve a mixture of these functions). Different functions can potentially cause the development of the same social behaviour. By identifying which function influences a particular social behaviour we can determine how that social behaviour will change with changing conditions, and which models are most pertinent. To test our approach we examined spider sociality, which has often been seen as the poor cousin to insect sociality. By using our approach we found that the group characteristics of eusocial insects is largely governed by the reproductive function of their groups, while the group characteristics of social spiders is largely governed by the foraging function of the group. This means that models relevant to insects may not be relevant to spiders. It also explains why eusocial insects have developed a strict caste system while spider societies are more egalitarian. We also used our approach to explain the differences between different types of spider groups. For example, differences in the characteristics of colonial and kleptoparasitic groups can be explained by differences in foraging methods, while differences between colonial and cooperative spiders can be explained by the role of the reproductive function in the formation of cooperative spider groups. Although the interactions within cooperative spider colonies are largely those of a foraging society, demographic traits and colony dynamics are strongly influenced by the reproductive function. We argue that functional explanations help to understand the social structure of spider groups and therefore the evolutionary potential for speciation in social spiders.

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Typically, cognitive abilities of humans have been attributed to their greatly expanded cortical mantle, granular prefrontal cortex (gPFC) in particular. Recently we have demonstrated systematic differences in microstructure of gPFC in different species. Specifically, pyramidal cells in adult human gPFC are considerably more spinous than those in the gPFC of the macaque monkey, which are more spinous than those in the gPFC of marmoset and owl monkeys. As most cortical dendritic spines receive at least one excitatory input, pyramidal cells in these different species putatively receive different numbers of inputs. These differences in the gPFC pyramidal cell phenotype may be of fundamental importance in determining the functional characteristics of prefrontal circuitry and hence the cognitive styles of the different species. However, it remains unknown as to why the gPFC pyramidal cell phenotype differs between species. Differences could be attributed to, among other things, brain size, relative size of gPFC, or the lineage to which the species belong. Here we investigated pyramidal cells in the dorsolateral gPFC of the prosimian galago to extend the basis for comparison. We found these cells to be less spinous than those in human, macaque, and marmoset. (c) 2005 Wiley-Liss, Inc.

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Cortical pyramidal cells, while having a characteristic morphology, show marked phenotypic variation in primates. Differences have been reported in their size, branching structure and spine density between cortical areas. In particular, there is a systematic increase in the complexity of the structure of pyramidal cells with anterior progression through occipito-temporal cortical visual areas. These differences reflect area-specific specializations in cortical circuitry, which are believed to be important for visual processing. However, it remains unknown as to whether these regional specializations in pyramidal cell structure are restricted to primates. Here we investigated pyramidal cell structure in the visual cortex of the tree shrew, including the primary (V1), second (V2) and temporal dorsal (TD) areas. As in primates, there was a trend for more complex branching structure with anterior progression through visual areas in the tree shrew. However, contrary to the trend reported in primates, cells in the tree shrew tended to become smaller with anterior progression through V1, V2 and TD. In addition, pyramidal cells in V1 of the tree shrew are more than twice as spinous as those in primates. These data suggest that variables that shape the structure of adult cortical pyramidal cells differ among species.

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The molecular clock does not tick at a uniform rate in all taxa but maybe influenced by species characteristics. Eusocial species (those with reproductive division of labor) have been predicted to have faster rates of molecular evolution than their nonsocial relatives because of greatly reduced effective population size; if most individuals in a population are nonreproductive and only one or few queens produce all the offspring, then eusocial animals could have much lower effective population sizes than their solitary relatives, which should increase the rate of substitution of nearly neutral mutations. An earlier study reported faster rates in eusocial honeybees and vespid wasps but failed to correct for phylogenetic nonindependence or to distinguish between potential causes of rate variation. Because sociality has evolved independently in many different lineages, it is possible to conduct a more wide-ranging study to test the generality of the relationship. We have conducted a comparative analysis of 25 phylogenetically independent pairs of social lineages and their nonsocial relatives, including bees, wasps, ants, termites, shrimps, and mole rats, using a range of available DNA sequences (mitochondrial and nuclear DNA coding for proteins and RNAs, and nontranslated sequences). By including a wide range of social taxa, we were able to test whether there is a general influence of sociality on rates of molecular evolution and to test specific predictions of the hypothesis: (1) that social species have faster rates because they have reduced effective population sizes; (2) that mitochondrial genes would show a greater effect of sociality than nuclear genes; and (3) that rates of molecular evolution should be correlated with the degree of sociality. We find no consistent pattern in rates of molecular evolution between social and nonsocial lineages and no evidence that mitochondrial genes show faster rates in social taxa. However, we show that the most highly eusocial Hymenoptera do have faster rates than their nonsocial relatives. We also find that social parasites (that utilize the workers from related species to produce their own offspring) have faster rates than their social relatives, which is consistent with an effect of lower effective population size on rate of molecular evolution. Our results illustrate the importance of allowing for phylogenetic nonindependence when conducting investigations of determinants of variation in rate of molecular evolution.

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To investigate the evolution pattern and phylogenetic utility of duplicate control regions (CRs) in mitochondrial (mt) genomes, we sequenced the entire mt genomes of three Ixodes species and part of the mt genomes of another I I species. All the species from the Australasian lineage have duplicate CRs, whereas the other species have one CR. Sequence analyses indicate that the two CRs of the Australasian Ixodes ticks have evolved in concert in each species. In addition to the Australasian Ixodes ticks, species from seven other lineages of metazoa also have mt genomes with duplicate CRs. Accumulated mtDNA sequence data from these metazoans and two recent experiments on replication of mt genomes in human cell lines with duplicate CRs allowed us to re-examine four intriguing questions about the presence of duplicate CRs in the mt genomes of metazoa: (1) Why do some mt genomes, but not others, have duplicate CRs? (2) How did mt genomes with duplicate CRs evolve? (3) How could the nucleotide sequences of duplicate CRs remain identical or very similar over evolutionary time? (4) Are duplicate CRs phylogenetic markers? It appears that mt genomes with duplicate CRs have a selective advantage in replication over mt genomes with one CR. Tandem duplication followed by deletion of genes is the most plausible mechanism for the generation of mt genomes with duplicate CRs. Once duplicate CRs occur in an mt genome, they tend to evolve in concert, probably by gene conversion. However, there are lineages where gene conversion may not always occur, and, thus, the two CRs may evolve independently in these lineages. Duplicate CRs have much potential as phylogenetic markers at low taxonomic levels, such as within genera, within families, or among families, but not at high taxonomic levels, such as among orders.

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Ketol-acid reductoisomerase (KARI; EC 1.1.1.86) catalyzes two steps in the biosynthesis of branched-chain amino acids. Amino acid sequence comparisons across species reveal that there are two types of this enzyme: a short form (Class 1) found in fungi and most bacteria, and a long form (Class 11) typical of plants. Crystal structures of each have been reported previously. However, some bacteria such as Escherichia coli possess a long form, where the amino acid sequence differs appreciably from that found in plants. Here, we report the crystal structure of the E. coli enzyme at 2.6 A resolution, the first three-dimensional structure of any bacterial Class 11 KARI. The enzyme consists of two domains, one with mixed alpha/beta structure, which is similar to that found in other pyridine nucleotide-dependent dehydrogenases. The second domain is mainly alpha-helical and shows strong evidence of internal duplication. Comparison of the active sites between KARI of E. coli, Pseudomonas aeruginosa, and spinach shows that most residues occupy conserved positions in the active site. E. coli KARI was crystallized as a tetramer, the likely biologically active unit. This contrasts with P. aeruginosa KARI, which forms a dodecamer, and spinach KARI, a dimer. In the E. coli KARI tetramer, a novel subunit-to-subunit interacting surface is formed by a symmetrical pair of bulbous protrusions.

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We review recent findings that, using fractal analysis, have demonstrated systematic regional and species differences in the branching complexity of neocortical pyramidal neurons. In particular, attention is focused on how fractal analysis is being applied to the study of specialization in pyramidal cell structure during the evolution of the primate cerebral cortex. These studies reveal variation in pyramidal cell phenotype that cannot be attributed solely to increasing brain volume. Moreover, the results of these studies suggest that the primate cerebral cortex is composed of neurons of different structural complexity. There is growing evidence to suggest that regional and species differences in neuronal structure influence function at both the cellular and circuit levels. These data challenge the prevailing dogma for cortical uniformity.

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The mammalian transcriptome contains many nonprotein-coding RNAs (ncRNAs), but most of these are of unclear significance and lack strong sequence conservation, prompting suggestions that they might be non-functional. However, certain long functional ncRNAs such as Air and Xist are also poorly conserved. In this article, we systematically analyzed the conservation of several groups of functional ncRNAs, including miRNAs, snoRNAs and longer ncRNAs whose function has been either documented or confidently predicted. As expected, miRNAs and snoRNAs were highly conserved. By contrast, the longer functional non-micro, non-sno ncRNAs were much less conserved with many displaying rapid sequence evolution. Our findings suggest that longer ncRNAs are under the influence of different evolutionary constraints and that the lack of conservation displayed by the thousands of candidate ncRNAs does not necessarily signify an absence of function.

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Mating preferences are common in natural populations, and their divergence among populations is considered an important source of reproductive isolation during speciation. Although mechanisms for the divergence of mating preferences have received substantial theoretical treatment, complementary experimental tests are lacking. We conducted a laboratory evolution experiment, using the fruit fly Drosophila serrata, to explore the role of divergent selection between environments in the evolution of female mating preferences. Replicate populations of D. serrata were derived from a common ancestor and propagated in one of three resource environments: two novel environments and the ancestral laboratory environment. Adaptation to both novel environments involved changes in cuticular hydrocarbons, traits that predict mating success in these populations. Furthermore, female mating preferences for these cuticular hydrocarbons also diverged among populations. A component of this divergence occurred among treatment environments, accounting for at least 17.4% of the among- population divergence in linear mating preferences and 17.2% of the among-population divergence in nonlinear mating preferences. The divergence of mating preferences in correlation with environment is consistent with the classic by- product model of speciation in which premating isolation evolves as a side effect of divergent selection adapting populations to their different environments.

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Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

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Niobium pentoxide reacts actively with concentrate NaOH solution under hydrothermal conditions at as low as 120 degrees C. The reaction ruptures the corner-sharing of NbO7 decahedra and NbO6 octahedra in the reactant Nb2O5, yielding various niobates, and the structure and composition of the niobates depend on the reaction temperature and time. The morphological evolution of the solid products in the reaction at 180 degrees C is monitored via SEM: the fine Nb2O5 powder aggregates first to irregular bars, and then niobate fibers with an aspect ratio of hundreds form. The fibers are microporous molecular sieve with a monoclinic lattice, Na2Nb2O6 center dot(2)/3H2O. The fibers are a metastable intermediate of this reaction, and they completely convert to the final product NaNbO3 Cubes in the prolonged reaction of 1 h. This study demonstrates that by carefully optimizing the reaction condition, we can selectively fabricate niobate structures of high purity, including the delicate microporous fibers, through a direct reaction between concentrated NaOH solution and Nb2O5. This synthesis route is simple and suitable for the large-scale production of the fibers. The reaction first yields poorly crystallized niobates consisting of edge-sharing NbO6 octahedra, and then the microporous fibers crystallize and grow by assembling NbO6 octahedra or clusters of NbO6 octahedra and NaO6 units. Thus, the selection of the fibril or cubic product is achieved by control of reaction kinetics. Finally, niobates with different structures exhibit remarkable differences in light absorption and photoluminescence properties. Therefore, this study is of importance for developing new functional materials by the wet-chemistry process.

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Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.