74 resultados para PHENOTYPIC CORRELATIONS

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Divergent selection acting on several different traits that cause multidimensional shifts are supposed to promote speciation, but the outcome of this process is highly dependent on the balance between the strength of selection vs. gene flow. Here, we studied a pair of sister species of Lake Victoria cichlids at a location where they hybridize and tested the hypothesis that divergent selection acting on several traits can maintain phenotypic differentiation despite gene flow. To explore the possible role of selection we tested for correlations between phenotypes and environment and compared phenotypic divergence (P-ST) with that based on neutral markers (F-ST). We found indications for disruptive selection acting on male breeding colour and divergent selection acting on several morphological traits. By performing common garden experiments we also separated the environmental and heritable components of divergence and found evidence for phenotypic plasticity in some morphological traits contributing to species differences.

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Heritable variation in plant phenotypes, and thus potential for evolutionary change, can in principle not only be caused by variation in DNA sequence, but also by underlying epigenetic variation. However, the potential scope of such phenotypic effects and their evolutionary significance are largely unexplored. Here, we conducted a glasshouse experiment in which we tested the response of a large number of epigenetic recombinant inbred lines (epiRILs) of Arabidopsis thaliana – lines that are nearly isogenic but highly variable at the level of DNA methylation – to drought and increased nutrient conditions. We found significant heritable variation among epiRILs both in the means of several ecologically important plant traits and in their plasticities to drought and nutrients. Significant selection gradients, that is, fitness correlations, of several mean traits and plasticities suggest that selection could act on this epigenetically based phenotypic variation. Our study provides evidence that variation in DNA methylation can cause substantial heritable variation of ecologically important plant traits, including root allocation, drought tolerance and nutrient plasticity, and that rapid evolution based on epigenetic variation alone should thus be possible.

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Recently, Petrella et al. described four patients with an unusual CD8+ lymphoid proliferation arising on the ear. These cases do not correspond clearly to any recognized category of cutaneous T-cell lymphoma (CTCL) described in the World Health Organization (WHO)/European Organization for Research and Treatment of Cancer (EORTC) 2005 classification.

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In multivariate time series analysis, the equal-time cross-correlation is a classic and computationally efficient measure for quantifying linear interrelations between data channels. When the cross-correlation coefficient is estimated using a finite amount of data points, its non-random part may be strongly contaminated by a sizable random contribution, such that no reliable conclusion can be drawn about genuine mutual interdependencies. The random correlations are determined by the signals' frequency content and the amount of data points used. Here, we introduce adjusted correlation matrices that can be employed to disentangle random from non-random contributions to each matrix element independently of the signal frequencies. Extending our previous work these matrices allow analyzing spatial patterns of genuine cross-correlation in multivariate data regardless of confounding influences. The performance is illustrated by example of model systems with known interdependence patterns. Finally, we apply the methods to electroencephalographic (EEG) data with epileptic seizure activity.

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Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.

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Over 75% of obese subjects fail to maintain their weight following weight loss interventions. We aimed to identify phenotypic and genetic markers associated with weight maintenance/regain following a dietary intervention.

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Congenital isolated ACTH deficiency (IAD) is a rare disease characterized by low plasma ACTH and cortisol levels and preservation of all other pituitary hormones. This condition was poorly defined before we identified TPIT, a T-box transcription factor with a specific role in differentiation of the corticotroph lineage in mice and humans, as its principal molecular cause.

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The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

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In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that these opposite correlations with different distributions undergo similar and significant neuronal developments with brain maturation.