981 resultados para motherhood - evolutionary theory
Resumo:
Robertsonian (Rb) fusions received large theoretical support for their role in speciation, but empirical evidence is often lacking. Here, we address the role of Rb rearrangements on the genetic differentiation of the karyotypically diversified group of shrews, Sorex araneus. We compared genetic structure between 'rearranged' and 'common' chromosomes in pairwise comparisons of five karyotypic taxa of the group. Considering all possible comparisons, we found a significantly greater differentiation at rearranged chromosomes, supporting the role of chromosomal rearrangements in the general genetic diversification of this group. Intertaxa structure and distance were larger across rearranged chromosomes for most of the comparisons, although these differences were not significant. This last result could be explained by the large variance observed among microsatellite-based estimates. The differences observed among the pairs of taxa analysed support the role of both the hybrid karyotypic complexity and the level of evolutionary divergence.
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Retroposed genes (retrogenes) originate via the reverse transcription of mature messenger RNAs from parental source genes and are therefore usually devoid of introns. Here, we characterize a particular set of mammalian retrogenes that acquired introns upon their emergence and thus represent rare cases of intron gain in mammals. We find that although a few retrogenes evolved introns in their coding or 3' untranslated regions (untranslated region, UTR), most introns originated together with untranslated exons in the 5' flanking regions of the retrogene insertion site. They emerged either de novo or through fusions with 5' UTR exons of host genes into which the retrogenes inserted. Generally, retrogenes with introns display high transcription levels and show broader spatial expression patterns than other retrogenes. Our experimental expression analyses of individual intron-containing retrogenes show that 5' UTR introns may indeed promote higher expression levels, at least in part through encoded regulatory elements. By contrast, 3' UTR introns may lead to downregulation of expression levels via nonsense-mediated decay mechanisms. Notably, the majority of retrogenes with introns in their 5' flanks depend on distant, sometimes bidirectional CpG dinucleotide-enriched promoters for their expression that may be recruited from other genes in the genomic vicinity. We thus propose a scenario where the acquisition of new 5' exon-intron structures was directly linked to the recruitment of distant promoters by these retrogenes, a process potentially facilitated by the presence of proto-splice sites in the genomic vicinity of retrogene insertion sites. Thus, the primary role and selective benefit of new 5' introns (and UTR exons) was probably initially to span the often substantial distances to potent CpG promoters driving retrogene transcription. Later in evolution, these introns then obtained additional regulatory roles in fine tuning retrogene expression levels. Our study provides novel insights regarding mechanisms underlying the origin of new introns, the evolutionary relevance of intron gain, and the origin of new gene promoters.
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The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.
Resumo:
Aquest treball elabora una proposta de traducció per al doblatge del capítol pilot de The Big Bang Theory, que combina llenguatge col•loquial i llenguatge científic.L’objectiu és doble: elaborar un llenguatge col•loquial creïble però a la vegada genuí i emprar els equivalents catalans adequats per als termes científics originals.
Resumo:
Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.
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Returns to scale to capital and the strength of capital externalities play a key role for the empirical predictions and policy implications of different growth theories. We show that both can be identified with individual wage data and implement our approach at the city-level using US Census data on individuals in 173 cities for 1970, 1980, and 1990. Estimation takes into account fixed effects, endogeneity of capital accumulation, and measurement error. We find no evidence for human or physical capital externalities and decreasing aggregate returns to capital. Returns to scale to physical and human capital are around 80 percent. We also find strong complementarities between human capital and labor and substantial total employment externalities.
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We propose a method to evaluate cyclical models which does not require knowledge of the DGP and the exact empirical specification of the aggregate decision rules. We derive robust restrictions in a class of models; use some to identify structural shocks and others to evaluate the model or contrast sub-models. The approach has good size and excellent power properties, even in small samples. We show how to examine the validity of a class of models, sort out the relevance of certain frictions, evaluate the importance of an added feature, and indirectly estimate structural parameters.
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166 countries have some kind of public old age pension. What economic forces create and sustain old age Social Security as a public program? Mulligan and Sala-i-Martin (1999b) document several of the internationally and historically common features of social security programs, and explore "political" theories of Social Security. This paper discusses the "efficiency theories", which view creation of the SS program as a full of partial solution to some market failure. Efficiency explanations of social security include the "SS as welfare for the elderly" the "retirement increases productivity to optimally manage human capital externalities", "optimal retirement insurance", the "prodigal father problem", the "misguided Keynesian", the "optimal longevity insurance", the "government economizing transaction costs", and the "return on human capital investment". We also analyze four "narrative" theories of social security: the "chain letter theory", the "lump of labor theory", the "monopoly capitalism theory", and the "Sub-but-Nearly-Optimal policy response to private pensions theory". The political and efficiency explanations are compared with the international and historical facts and used to derive implications for replacing the typical pay-as-you-go system with a forced savings plan. Most of the explanations suggest that forced savings does not increase welfare, and may decrease it.
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We analyze the role of commitment in pre-play communication for ensuring efficient evolutionarily stable outcomes in coordination games. All players are a priori identical as they are drawn from the same population. In games where efficient outcomes can be reached by players coordinating on the same action we find commitment to be necessary to enforce efficiency. In games where efficienct outcomes only result from play of different actions, communication without commitment is most effective although efficiency can no longer be guaranteed. Only when there are many messages then inefficient outcomes are negligible as their basins of attraction become very small.
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We present a theory of choice among lotteries in which the decision maker's attention is drawn to (precisely defined) salient payoffs. This leads the decision maker to a context-dependent representation of lotteries in which true probabilities are replaced by decision weights distorted in favor of salient payoffs. By endogenizing decision weights as a function of payoffs, our model provides a novel and unified account of many empirical phenomena, including frequent risk-seeking behavior, invariance failures such as the Allais paradox, and preference reversals. It also yields new predictions, including some that distinguish it from Prospect Theory, which we test.
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Trait decoupling, wherein evolutionary release of constraints permits specialization of formerly integrated structures, represents a major conceptual framework for interpreting patterns of organismal diversity. However, few empirical tests of this hypothesis exist. A central prediction, that the tempo of morphological evolution and ecological diversification should increase following decoupling events, remains inadequately tested. In damselfishes (Pomacentridae), a ceratomandibular ligament links the hyoid bar and lower jaws, coupling two main morphofunctional units directly involved in both feeding and sound production. Here, we test the decoupling hypothesis by examining the evolutionary consequences of the loss of the ceratomandibular ligament in multiple damselfish lineages. As predicted, we find that rates of morphological evolution of trophic structures increased following the loss of the ligament. However, this increase in evolutionary rate is not associated with an increase in trophic breadth, but rather with morphofunctional specialization for the capture of zooplanktonic prey. Lineages lacking the ceratomandibular ligament also shows different acoustic signals (i.e. higher variation of pulse periods) from others, resulting in an increase of the acoustic diversity across the family. Our results support the idea that trait decoupling can increase morphological and behavioural diversity through increased specialization rather than the generation of novel ecotypes.
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When individuals in a population can acquire traits through learning, each individual may express a certain number of distinct cultural traits. These traits may have been either invented by the individual himself or acquired from others in the population. Here, we develop a game theoretic model for the accumulation of cultural traits through individual and social learning. We explore how the rates of innovation, decay, and transmission of cultural traits affect the evolutionary stable (ES) levels of individual and social learning and the number of cultural traits expressed by an individual when cultural dynamics are at a steady-state. We explore the evolution of these phenotypes in both panmictic and structured population settings. Our results suggest that in panmictic populations, the ES level of learning and number of traits tend to be independent of the social transmission rate of cultural traits and is mainly affected by the innovation and decay rates. By contrast, in structured populations, where interactions occur between relatives, the ES level of learning and the number of traits per individual can be increased (relative to the panmictic case) and may then markedly depend on the transmission rate of cultural traits. This suggests that kin selection may be one additional solution to Rogers's paradox of nonadaptive culture.