783 resultados para roost selection


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The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDP) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation map to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and responds differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function - enabling information is encoded in IDPs.

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The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

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We study a dynamic model where growth requires both long-term investmentand the selection of talented managers. When ability is not ex-ante observable and contracts are incomplete, managerial selection imposes a cost, as managers facing the risk ofbeing replaced choose a sub-optimally low level of long-term investment. This generates atrade-off between selection and investment that has implications for the choice of contractualrelationships and institutions. Our analysis shows that rigid long-term contracts sacrificingmanagerial selection may prevail at early stages of economic development and when heterogeneity in ability is low. As the economy grows, however, knowledge accumulation increasesthe return to talent and makes it optimal to adopt flexible contractual relationships, wheremanagerial selection is implemented even at the cost of lower investment. Measures of investor protection aimed at limiting the bargaining power of managers improve selection undershort-term contract. Given that knowledge accumulation raises the value of selection, theoptimal level of investor protection increases with development.

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The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

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The objective of this work was to propose a new selection strategy for the initial stages of sugarcane improvement, based on the methodology 'simulated individual BLUP (BLUPIS)', which promotes a dynamic allocation of individuals selected in each full-sib family, using BLUP as a base for both the genotypic effects of the referred families and plot effects. The method proposed applies to single full-sib families or those obtained from unbalanced or balanced diallel crosses, half-sib families and self-pollinated families. BLUPIS indicates the number of individuals to be selected within each family, the total number of clones to be advanced, and the number of families to contribute with selected individuals. Correlation between BLUPIS and true BLUP was 0.96, by method validation. Additionally, BLUPIS allows the identification of which replication contains the best individuals of each family.

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Theory predicts that if most mutations are deleterious to both overall fitness and condition-dependent traits affecting mating success, sexual selection will purge mutation load and increase nonsexual fitness. We explored this possibility with populations of mutagenized Drosophila melanogaster exhibiting elevated levels of deleterious variation and evolving in the presence or absence of male-male competition and female choice. After 60 generations of experimental evolution, monogamous populations exhibited higher total reproductive output than polygamous populations. Parental environment also affected fitness measures - flies that evolved in the presence of sexual conflict showed reduced nonsexual fitness when their parents experienced a polygamous environment, indicating trans-generational effects of male harassment and highlighting the importance of a common garden design. This cost of parental promiscuity was nearly absent in monogamous lines, providing evidence for the evolution of reduced sexual antagonism. There was no overall difference in egg-to-adult viability between selection regimes. If mutation load was reduced by the action of sexual selection in this experiment, the resultant gain in fitness was not sufficient to overcome the costs of sexual antagonism.

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Background: The ratio of the rates of non-synonymous and synonymous substitution (d(N)/d(S)) is commonly used to estimate selection in coding sequences. It is often suggested that, all else being equal, d(N)/d(S) should be lower in populations with large effective size (Ne) due to increased efficacy of purifying selection. As N-e is difficult to measure directly, life history traits such as body mass, which is typically negatively associated with population size, have commonly been used as proxies in empirical tests of this hypothesis. However, evidence of whether the expected positive correlation between body mass and d(N)/d(S) is consistently observed is conflicting. Results: Employing whole genome sequence data from 48 avian species, we assess the relationship between rates of molecular evolution and life history in birds. We find a negative correlation between dN/dS and body mass, contrary to nearly neutral expectation. This raises the question whether the correlation might be a method artefact. We therefore in turn consider non-stationary base composition, divergence time and saturation as possible explanations, but find no clear patterns. However, in striking contrast to d(N)/d(S), the ratio of radical to conservative amino acid substitutions (K-r/K-c) correlates positively with body mass. Conclusions: Our results in principle accord with the notion that non-synonymous substitutions causing radical amino acid changes are more efficiently removed by selection in large populations, consistent with nearly neutral theory. These findings have implications for the use of d(N)/d(S) and suggest that caution is warranted when drawing conclusions about lineage-specific modes of protein evolution using this metric.

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The objective of this work was to validate microsatellite markers associated with resistance to soybean cyst nematode (Heterodera glycines Ichinohe) races 3 and 14, in soybean (Glycine max L.) genotypes, for use in marker-assisted selection (MAS) programs. Microsatellites of soybean linkage groups A2, D2 and G were tested in two populations, and their selection efficiencies were determined. The populations were 65 F2:3 families from Msoy8001 (resistant) x Conquista (susceptible) cross, and 66 F2:3 families of S5995 (resistant) x Renascença (susceptible) cross, evaluated for resistance to races 3 and 14, respectively. Families with female index up to 30% were considered moderately resistant. Markers of A2 and G linkage groups were associated with resistance to race 3. Markers Satt309 and GMENOD2B explained the greatest proportion of phenotypic variance in the different groups. The combinations Satt309+GMENOD2B and Satt309+Satt187 presented 100% selection efficiency. Resistance to race 14 was associated with markers of G linkage group, and selection efficiency in the Satt309+Satt356 combination was 100%. The selection differential obtained by phenotypic and marker assisted selection showed that both can result in similar gains.

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Modeling the mechanisms that determine how humans and other agents choose among different behavioral and cognitive processes-be they strategies, routines, actions, or operators-represents a paramount theoretical stumbling block across disciplines, ranging from the cognitive and decision sciences to economics, biology, and machine learning. By using the cognitive and decision sciences as a case study, we provide an introduction to what is also known as the strategy selection problem. First, we explain why many researchers assume humans and other animals to come equipped with a repertoire of behavioral and cognitive processes. Second, we expose three descriptive, predictive, and prescriptive challenges that are common to all disciplines which aim to model the choice among these processes. Third, we give an overview of different approaches to strategy selection. These include cost‐benefit, ecological, learning, memory, unified, connectionist, sequential sampling, and maximization approaches. We conclude by pointing to opportunities for future research and by stressing that the selection problem is far from being resolved.

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The objectives of this work were to analyze theoretical genetic gains of maize due to recurrent selection among full-sib and half-sib families, obtained by Design I, Full-Sib Design and Half-Sib Design, and genotypic variability and gene loss with long term selection. The designs were evaluated by simulation, based on average estimated gains after ten selection cycles. The simulation process was based on seven gene systems with ten genes (with distinct degrees of dominance), three population classes (with different gene frequencies), under three environmental conditions (heritability values), and four selection strategies. Each combination was repeated ten times, amounting to 25, 200 simulations. Full-sib selection is generally more efficient than half-sib selection, mainly with favorable dominant genes. The use of full-sib families derived by Design I is generally more efficient than using progenies obtained by Full-Sib Design. Using Design I with 50 males and 200 females (effective size of 160) did not result in improved populations with minimum genotypic variability. In the populations with lower effective size (160 and 400) the loss of favorable genes was restricted to recessive genes with reduced frequencies.

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The objective of this work was to determine soybean resistance inheritance to Heterodera glycines Ichinohe (soybean cyst nematode - SCN) races 3 and 9, as well as to evaluate the efficiency of direct and indirect selection in a soybean population of 112 recombinant inbred lines (RIL) derived from the resistant cultivar Hartwig. The experiment was conducted in a completely randomized design, in Londrina, PR, Brazil. The estimated narrow-sense heritabilities for resistance to races 3 and 9 were 80.67 and 77.97%. The genetic correlation coefficient (r g = 0.17; p<0.01) shows that some genetic components of resistance to these two races are inherited together. The greatest genetic gain by indirect selection was obtained to race 9, selecting to race 3 due to simpler inheritance of resistance to race 9 and not because these two races share common resistance genes. The resistance of cultivar Hartwig to races 3 and 9 is determined by 4 and 2 genes, respectively. One of these genes confers resistance to both races, explaining a fraction of the significant genetic correlation found between resistance to these SCN races. The inheritance pattern described indicates that selection for resistance to SCN must be performed for each race individually.

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The objective of this work was to evaluate the potential of allohexaploid pearl millet x elephantgrass (HGL) population for a recurrent selection program through open-pollinated progenies. Seventy-eight progenies, one representative sample of the population, and two commercial cultivars, Pioneiro and Paraíso, were evaluated in a 9x9 triple lattice design, in two sites. Plant height and dry matter yield were evaluated in three and four cuts, respectively. For plant height, the 17 best progenies were similar to both commercial controls, while for dry matter yield they were higher than 'Paraíso' and lower than 'Pioneiro'. The correlation between progenies and cuts indicated that the fourth cut represents the mean of all cuts, and the possibility of using early selection. Heritability estimates considering cuts and sites were 56.9% for plant height and 58.8% for dry matter yield, and the expected response to selection was 23.4% for dry matter yield and 18.1% for plant height. These results demonstrate the promising HGL population potential for a recurrent selection program.

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Positive selection is widely estimated from protein coding sequence alignments by the nonsynonymous-to-synonymous ratio omega. Increasingly elaborate codon models are used in a likelihood framework for this estimation. Although there is widespread concern about the robustness of the estimation of the omega ratio, more efforts are needed to estimate this robustness, especially in the context of complex models. Here, we focused on the branch-site codon model. We investigated its robustness on a large set of simulated data. First, we investigated the impact of sequence divergence. We found evidence of underestimation of the synonymous substitution rate for values as small as 0.5, with a slight increase in false positives for the branch-site test. When dS increases further, underestimation of dS is worse, but false positives decrease. Interestingly, the detection of true positives follows a similar distribution, with a maximum for intermediary values of dS. Thus, high dS is more of a concern for a loss of power (false negatives) than for false positives of the test. Second, we investigated the impact of GC content. We showed that there is no significant difference of false positives between high GC (up to similar to 80%) and low GC (similar to 30%) genes. Moreover, neither shifts of GC content on a specific branch nor major shifts in GC along the gene sequence generate many false positives. Our results confirm that the branch-site is a very conservative test.