969 resultados para Genetic information


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Eukaryotic phenotypic diversity arises from multitasking of a core proteome of limited size. Multitasking is routine in computers, as well as in other sophisticated information systems, and requires multiple inputs and outputs to control and integrate network activity. Higher eukaryotes have a mosaic gene structure with a dual output, mRNA (protein-coding) sequences and introns, which are released from the pre-mRNA by posttranscriptional processing. Introns have been enormously successful as a class of sequences and comprise up to 95% of the primary transcripts of protein-coding genes in mammals. In addition, many other transcripts (perhaps more than half) do not encode proteins at all, but appear both to be developmentally regulated and to have genetic function. We suggest that these RNAs (eRNAs) have evolved to function as endogenous network control molecules which enable direct gene-gene communication and multitasking of eukaryotic genomes. Analysis of a range of complex genetic phenomena in which RNA is involved or implicated, including co-suppression, transgene silencing, RNA interference, imprinting, methylation, and transvection, suggests that a higher-order regulatory system based on RNA signals operates in the higher eukaryotes and involves chromatin remodeling as well as other RNA-DNA, RNA-RNA, and RNA-protein interactions. The evolution of densely connected gene networks would be expected to result in a relatively stable core proteome due to the multiple reuse of components, implying,that cellular differentiation and phenotypic variation in the higher eukaryotes results primarily from variation in the control architecture. Thus, network integration and multitasking using trans-acting RNA molecules produced in parallel with protein-coding sequences may underpin both the evolution of developmentally sophisticated multicellular organisms and the rapid expansion of phenotypic complexity into uncontested environments such as those initiated in the Cambrian radiation and those seen after major extinction events.

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MC1R gene variants have previously been associated with red hair and fair skin color, moreover skin ultraviolet sensitivity and a strong association with melanoma has been demonstrated for three variant alleles that are active in influencing pigmentation: Arg151Cys, Arg160Trp, and Asp294His. This study has confirmed these pigmentary associations with MC1R genotype in a collection of 220 individuals drawn from the Nambour community in Queensland, Australia, 111 of whom were at high risk and 109 at low risk of basal cell squamous cell carcinoma. Comparative allele frequencies for nine MC1R variants that have been reported in the Caucasian population were determined for these two groups, and an association between prevalence of basal cell carcinoma, squamous cell carcinoma, solar keratosis and the same three active MC1R variant alleles was demonstrated [odds ratio=3.15 95% CI (1.7, 5.82)]. Three other commonly occurring variant alleles: Val60Leu, Val92Met, and Arg163Gln were identified as having a minimal impact on pigmentation phenotype as well as basal cell carcinoma and squamous cell carcinoma risk. A significant heterozygote effect was demonstrated where individuals carrying a single MC1R variant allele were more likely to have fair and sun sensitive skin as well as carriage of a solar lesion when compared with those individuals with a consensus MC1R genotype. After adjusting for the effects of pigmentation on the association between MC1R variant alleles and basal cell carcinoma and squamous cell carcinoma risk, the association persisted, confirming that presence of at least one variant allele remains informative in terms of predicting risk for developing a solar-induced skin lesion beyond that information gained through observation of pigmentation phenotype.

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Goal-directed, coordinated movements in humans emerge from a variety of constraints that range from 'high-level' cognitive strategies based oil perception of the task to 'low-level' neuromuscular-skeletal factors such as differential contributions to coordination from flexor and extensor muscles. There has been a tendency in the literature to dichotomize these sources of constraint, favouring one or the other rather than recognizing and understanding their mutual interplay. In this experiment, subjects were required to coordinate rhythmic flexion and extension movements with an auditory metronome, the rate of which was systematically increased. When subjects started in extension on the beat of the metronome, there was a small tendency to switch to flexion at higher rates, but not vice versa. When subjects: were asked to contact a physical stop, the location of which was either coincident with or counterphase to the auditor) stimulus, two effects occurred. When haptic contact was coincident with sound, coordination was stabilized for both flexion and extension. When haptic contact was counterphase to the metronome, coordination was actually destabilized, with transitions occurring from both extension to flexion on the beat and from flexion to extension on the beat. These results reveal the complementary nature of strategic and neuromuscular factors in sensorimotor coordination. They also suggest the presence of a multimodal neural integration process-which is parametrizable by rate and context - in which intentional movement, touch and sound are bound into a single, coherent unit.

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In population pharmacokinetic studies, the precision of parameter estimates is dependent on the population design. Methods based on the Fisher information matrix have been developed and extended to population studies to evaluate and optimize designs. In this paper we propose simple programming tools to evaluate population pharmacokinetic designs. This involved the development of an expression for the Fisher information matrix for nonlinear mixed-effects models, including estimation of the variance of the residual error. We implemented this expression as a generic function for two software applications: S-PLUS and MATLAB. The evaluation of population designs based on two pharmacokinetic examples from the literature is shown to illustrate the efficiency and the simplicity of this theoretic approach. Although no optimization method of the design is provided, these functions can be used to select and compare population designs among a large set of possible designs, avoiding a lot of simulations.

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When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

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There is overwhelming evidence for the existence of substantial genetic influences on individual differences in general and specific cognitive abilities, especially in adults. The actual localization and identification of genes underlying variation in cognitive abilities and intelligence has only just started, however. Successes are currently limited to neurological mutations with rather severe cognitive effects. The current approaches to trace genes responsible for variation in the normal ranges of cognitive ability consist of large scale linkage and association studies. These are hampered by the usual problems of low statistical power to detect quantitative trait loci (QTLs) of small effect. One strategy to boost the power of genomic searches is to employ endophenotypes of cognition derived from the booming field of cognitive neuroscience This special issue of Behavior Genetics reports on one of the first genome-wide association studies for general IQ. A second paper summarizes candidate genes for cognition, based on animal studies. A series of papers then introduces two additional levels of analysis in the ldquoblack boxrdquo between genes and cognitive ability: (1) behavioral measures of information-processing speed (inspection time, reaction time, rapid naming) and working memory capacity (performance on on single or dual tasks of verbal and spatio-visual working memory), and (2) electrophyiosological derived measures of brain function (e.g., event-related potentials). The obvious way to assess the reliability and validity of these endophenotypes and their usefulness in the search for cognitive ability genes is through the examination of their genetic architecture in twin family studies. Papers in this special issue show that much of the association between intelligence and speed-of-information processing/brain function is due to a common gene or set of genes, and thereby demonstrate the usefulness of considering these measures in gene-hunting studies for IQ.

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Around 98% of all transcriptional output in humans is noncoding RNA. RNA-mediated gene regulation is widespread in higher eukaryotes and complex genetic phenomena like RNA interference, co-suppression, transgene silencing, imprinting, methylation, and possibly position-effect variegation and transvection, all involve intersecting pathways based on or connected to RNA signaling. I suggest that the central dogma is incomplete, and that intronic and other non-coding RNAs have evolved to comprise a second tier of gene expression in eukaryotes, which enables the integration and networking of complex suites of gene activity. Although proteins are the fundamental effectors of cellular function, the basis of eukaryotic complexity and phenotypic variation may lie primarily in a control architecture composed of a highly parallel system of trans-acting RNAs that relay state information required for the coordination and modulation of gene expression, via chromatin remodeling, RNA-DNA, RNA-RNA and RNA-protein interactions. This system has interesting and perhaps informative analogies with small world networks and dataflow computing.

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The cotton bollworm (Helicoverpa armigera) prefers the common sowthistle (Sonchus oleraceus L.) to cotton (Gossypium hirsutum L.), sorghum (Sorghum bicolor L.) and maize (Zea mays L.) for oviposition in the field in Australia. Using the common sowthistle and cotton as host plants, we carried out this study to evaluate genetic variation in both oviposition preference and larval growth and genetic correlation between maternal preference and larval performance. There was a significant genetic component of phenotypic variation in both characters, and the heritability of oviposition preference was estimated as 0.602. Helicoverpa armigera larvae survived slightly better and grew significantly faster on common sowthistle than on cotton, but genetic correlation between maternal preference and larval growth performance was not detectable. Instead, larval growth performance on the two hosts changed with families, which renders the interaction between family and host plant significant. As a result, the genetic correlation between mean values of larval growth across the two host species was not different from zero. These results are discussed in the context of the relationship between H. armigera and the common sowthistle and the polyphagous behaviour of this insect in general.

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Dispersal, or the amount of dispersion between an individual's birthplace and that of its offspring, is of great importance in population biology, behavioural ecology and conservation, however, obtaining direct estimates from field data on natural populations can be problematic. The prickly forest skink, Gnypetoscincus queenslandiae, is a rainforest endemic skink from the wet tropics of Australia. Because of its log-dwelling habits and lack of definite nesting sites, a demographic estimate of dispersal distance is difficult to obtain. Neighbourhood size, defined as 4 piD sigma (2) (where D is the population density and sigma (2) the mean axial squared parent-offspring dispersal rate), dispersal and density were estimated directly and indirectly for this species using mark-recapture and microsatellite data, respectively, on lizards captured at a local geographical scale of 3 ha. Mark-recapture data gave a dispersal rate of 843 m(2)/generation (assuming a generation time of 6.5 years), a time-scaled density of 13 635 individuals * generation/km(2) and, hence, a neighbourhood size of 144 individuals. A genetic method based on the multilocus (10 loci) microsatellite genotypes of individuals and their geographical location indicated that there is a significant isolation by distance pattern, and gave a neighbourhood size of 69 individuals, with a 95% confidence interval between 48 and 184. This translates into a dispersal rate of 404 m(2)/generation when using the mark-recapture density estimation, or an estimate of time-scaled population density of 6520 individuals * generation/km(2) when using the mark-recapture dispersal rate estimate. The relationship between the two categories of neighbourhood size, dispersal and density estimates and reasons for any disparities are discussed.