Stability of the G-matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift

Abstract. Quantitative genetics theory provides a framework that predicts the effects of selection on a phenotype consisting of a suite of complex traits. However, the ability of existing theory to reconstruct the history of selection or to predict the future trajectory of evolution depends upon the evolutionary dynamics of the genetic variance-covariance matrix (G-matrix). Thus, the central focus of the emerging field of comparative quantitative genetics is the evolution of the G-matrix. Existing analytical theory reveals little about the dynamics of G, because the problem is too complex to be mathematically tractable. As a first step toward a predictive theory of G-matrix evolution, our goal was to use stochastic computer models to investigate factors that might contribute to the stability of G over evolutionary time. We were concerned with the relatively simple case of two quantitative traits in a population experiencing stabilizing selection, pleiotropic mutation, and random genetic drift. Our results show that G-matrix stability is enhanced by strong correlational selection and large effective population size. In addition, the nature of mutations at pleiotropic loci can dramatically influence stability of G. In particular, when a mutation at a single locus simultaneously changes the value of the two traits (due to pleiotropy) and these effects are correlated, mutation can generate extreme stability of G. Thus, the central message of our study is that the empirical question regarding G-matrix stability is not necessarily a general question of whether G is stable across various taxonomic levels. Rather, we should expect the G-matrix to be extremely stable for some suites of characters and unstable for others over similar spans of evolutionary time.     

Correlated motion and oscillation of neighboring cells in vitro

It has long been realized that fibroblastic and epithelial cells establish recognizable patterns in tissue culture. This behavior implies that neighboring cells interact with one another to produce organized populations. Interaction between cells that are separated by many intervening cells is also possible and is demonstrated here using a special configuration of a biosensor referred to as electric cell-substrate impedance sensing (ECIS). Normally the electrical impedance of a single electrode covered with a confluent cell layer is measured, and the morphological changes of the cells are reflected in the impedance. In this case the cells are cultured on two closely spaced electrodes whose impedances are measured independently as a function of time, and communication between the cell populations is revealed as a correlation between these two time series. We also report for the first time another striking manifestation of dynamic cell interaction, where confluent layers of Madin-Darby canine kidney cells (MDCK) on a single electrode are observed to oscillate in synchrony with a period of approximately 2.5 h.     

Novel 2D and 3D multiple-quantum bi-directional HCNCH experiments for the correlation of ribose and base protons/carbons in 13C/15N labeled RNA

Multiple-quantum 2D and 3D bi-directional HCNCH experiments are presented for the correlation of base and ribose protons/carbons in ¹³C/¹⁵N labeled HIV-1 TAR RNA. In both 2D and 3D experiments, the magnetization of H1 is transferred to H6/H8 and H1 through H1-C1-N1/9-C6/8-H6/8 and H1-C1-N1/9-C1-H1 pathways, and the magnetization of H6/8 is transferred to H1 and H6/8 through H6/8-C6/8-N1/9-C1-H1 and H6/8-C6/8-N1/9-C6/8-H6/8 pathways. Chemical shifts of four different nuclei (H1, C1, C6/8 and H6/8) are sampled in the 2D experiment. The correlation of base and ribose protons/carbons is established by the rectangular arrangement of crossover and out-and-back peaks in the proton/carbon correlated spectrum. The rectangular connections can be further resolved using the nitrogen dimension in a ¹H/¹³C/¹⁵N 3D experiment. Furthermore, by taking advantage of the well separated chemical shifts of N1 (pyrimidine) and N9 (purine), the 2D spectrum can be simplified into two sub-spectra based on their base type. Both experiments were tested on a ¹³C/¹⁵N labeled 27-mer HIV-1 TAR RNA containing a UUCG hairpin loop.     

Measuring antibody affinity and performing immunoassay at the single molecule level

Fluorescence correlation spectroscopy (FCS) enables direct observation of the translational diffusion of single fluorescent molecules in solution. When fluorescent hapten binds to antibody, analysis of FCS data yields the fractional amounts of free and bound hapten, allowing determination of the equilibrium binding constant. Equilibrium dissociation constants of anti-digoxin antibodies and corresponding fluorescein-labeled digoxigenin obtained by FCS and fluorescence polarization measurements are identical. It is also possible to follow a competitive displacement of the tracer from the antibody by unlabeled hapten using FCS in an immunoassay format. The fluorescence polarization immunoassay for vancomycin detection was used to test the FCS approach. Fitting of the FCS data for the molar fractions of free and bound fluorescein-labeled vancomycin yielded a calibration curve which could serve for determination of the vancomycin concentration in biological samples.     

Sesquiterpene constituents in Petasites hybridus

The essential oil of the rhizomes of Petasites hybridus (Asteraceae) was investigated by gas chromatography, mass spectrometry, 1- and 2-dimensional NMR techniques and chemical correlations. Two new sesquiterpene hydrocarbons, petasitene and pethybrene, could be identified. Petasitene is the parent sesquiterpene hydrocarbon to the known norsesquiterpene albene. The absolute configuration of petasitene could be assigned by conversion of natural albene to petasitene by partial synthesis. Pethybrene is a tricyclic sesquiterpene hydrocarbon, which rearranges to the structurally related alpha-isocomene under acidic conditions. Several sesquiterpenes were isolated from the hydrodistillation products of Petasites hybridus and investigated by spectroscopic methods and chemical correlations     

Selenium levels in human plasma and hair in northern poland

The aim of this study was to (1) estimate the concentration of selenium in the plasma of 146 residents (65 men and 81 women) and in the hair of 34 persons from the Gdańsk region in northern Poland, aged 19–70 and (2) compare the obtained results with data corresponding to healthy populations living in different European countries. Selenium in plasma was determined by atomic absorption spectrometry using the hydride generation method. The mean selenium concentration in plasma of the investigated persons was 73.3 ± 14.1 μg/L, 76.7 ± 13.2 μg/L in men, and 70.4 ± 14.7 μg/L in women. No age — dependent differences in plasma selenium were found in the investigated population. In 20% of the investigated persons, the selenium level in plasma was lower than 60 μg/L. The mean selenium concentration in hair was 0.30 ± 0.11 μg/g. A positive, statistically significant correlation between selenium concentrations in the plasma and hair of the investigated persons was found. The obtained results indicate that the selenium level in significant part of this population is suboptimal and should be elevated by supplementation with this element.     

Correlation between serum cholesterols and trace element uptake in liver,kidney, and blood of hypercholesterolemic mice

The radioactive multitracer technique was applied to the simultaneous determination of the uptake of 17 trace elements (Be, Na, Sc, V, Cr, Mn, Fe, Co, Zn, As, Se, Rb, Sr, Y, Zr, Nb, and Ru) in the liver, kidney, and blood of hypercholesterolemic model mice. The uptakes of Be, Sc, V, Cr, Fe, As, Rb, Y, Zr, Nb, and Ru in liver increased with an increasing feeding period of a cholesterol-rich diet, whereas the uptakes of Zn and Se decreased. Feeding of the diet resulted in a marked increase in serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol. The metabolism of trace elements between cholesterolemic and normal mice was compared with respect to their serum cholesterol levels. A significant positive correlation was found between the concentration of serum triglycerides and liver uptakes of Cr, Fe, and As and a negative correlation for the uptake of Zn. A significant positive correlation was found between the concentrations of serum high- and low-density lipoprotein cholesterols and kidney uptakes of Cr and Rb. A negative correlation was found between the uptake of Be in the blood and the concentration of serum triglycerides. These results suggest that cholesterolemia have some specific effects on the metabolism of some elements.     

Overall concordance correlation coefficient for evaluating agreement among multiple observers

Accurate and precise measurement is an important component of any proper study design. As elaborated by Lin (1989, Biometrics 45, 255-268), the concordance correlation coefficient (CCC) is more appropriate than other indices for measuring agreement when the variable of interest is continuous. However, this agreement index is defined in the context of comparing two fixed observers. In order to use multiple observers in a study involving large numbers of subjects, there is a need to assess agreement among these multiple observers. In this article, we present an overall CCC (OCCC) in terms of the interobserver variability for assessing agreement among multiple fixed observers. The OCCC turns out to be equivalent to the generalized CCC (King and Chinchilli, 2001, Statistics in Medicine 20, 2131-2147; Lin, 1989; Lin, 2000, Biometrics 56, 324-325) when the squared distance function is used. We evaluated the OCCC through generalized estimating equations (Barnhart and Williamson, 2001, Biometrics 57, 931-940) and U-statistics (King and Chinchilli, 2001) for inference. This article offers the following important points. First, it addresses the precision and accuracy indices as components of the OCCC. Second, it clarifies that the OCCC is the weighted average of all pairwise CCCs. Third, it is intuitively defined in terms of interobserver variability. Fourth, the inference approaches of GEE and the U-statistics are compared via simulations for small samples. Fifth, we illustrate the use of the OCCC by two medical examples with the GEE, U-statistics, and bootstrap approaches.     

Gamma irradiation and cellular damage in Kocuria rosea: investigation by one- and two-dimensional infrared spectroscopy

Fourier transform infrared (FT-IR) spectroscopy was used to investigate the radiation-induced effects on Kocuria rosea. Bacterial suspensions at the stationary phase were exposed to increasing doses of gamma radiation. In the region 1350-840cm(-1), assigned to phosphodiester backbone, nucleic acids, and sugar rings, the radical damaging effects were dose-dependent, with the first threshold at 2.75kGy and the second at 13.75kGy inducing more striking spectral variations. Postirradiation reincubation did not significantly affect the biomolecular response, except in the spectral range 1100-1000cm(-1). These observations suggest the occurrence of new phylogenetic characteristics for K. rosea following irradiation. Moreover, two-dimensional analysis was used to highlight correlated evolutions of molecular species as radical aggression increased. The results point to an evolutionary scheme during the time course of irradiation. Thus, one- and two-dimensional IR analyses are convenient means of investigating the metabolic events following oxidative stress generated by either chemical or physical agents.     

Characteristics of trajectory in the migration of Amoeba proteus

Summary. We investigated the behavior of migration of Amoeba proteus in an isotropic environment. We found that the trajectory in the migration of A. proteus is smooth in the observation time of 500-1000 s, but its migration every second (the cell velocity) on the trajectory randomly changes. Stochastic analysis of the cell velocity and the turn angle of the trajectory has shown that the histograms of the both variables well fit to Gaussian curves. Supposing a simple model equation for the cell motion, we have estimated the motive force of the migrating cell, which is of the order of piconewton. Furthermore, we have found that the cell velocity and the turn angle have a negative cross-correlation coefficient, which suggests that the amoeba explores better environment by changing frequently its migrating direction at a low speed and it moves rectilinearly to the best environment at a high speed. On the other hand, the model equation has simulated the negative correlation between the cell velocity and the turn angle. This indicates that the apparently rational behavior comes from intrinsic characteristics in the dynamical system where the motive force is not torquelike.