Predicting evolution of floral traits associated with mating system in a natural plant population

Evolution of floral traits requires that they are heritable, that they affect fitness, and that they are not constrained by genetic correlations. These prerequisites have only rarely been examined in natural populations. For Mimulus guttatus, we found by using the Riska-method that corolla width, anther length, ovary length and number of red dots on the corolla were heritable in a natural population. Seed production (maternal fitness) was directly positively affected by corolla width and anther size, and indirectly so by ovary length and number of red dots on the corolla. The siring success (paternal fitness), as estimated from allozyme data, was directly negatively affected by anther-stigma separation, and indirectly so by the corolla length-width ratio. Genetic correlations, estimated with the Lynch-method, were positive between floral size measures. We predict that larger flowers with larger reproductive organs, which generally favour outcrossing, will evolve in this natural population of M. guttatus.     

Comparison of (13)C(alpha)H and (15)NH backbone dynamics in protein GB1

This study presents a site-resolved experimental view of backbone C(alpha)H and NH internal motions in the 56-residue immunoglobulin-binding domain of streptococcal protein G, GB1. Using (13)C(alpha)H and (15)NH NMR relaxation data [T(1), T(2), and NOE] acquired at three resonance frequencies ((1)H frequencies of 500, 600, and 800 MHz), spectral density functions were calculated as F(omega) = 2omegaJ(omega) to provide a model-independent way to visualize and analyze internal motional correlation time distributions for backbone groups in GB1. Line broadening in F(omega) curves indicates the presence of nanosecond time scale internal motions (0.8 to 5 nsec) for all C(alpha)H and NH groups. Deconvolution of F(omega) curves effectively separates overall tumbling and internal motional correlation time distributions to yield more accurate order parameters than determined by using standard model free approaches. Compared to NH groups, C(alpha)H internal motions are more broadly distributed on the nanosecond time scale, and larger C(alpha)H order parameters are related to correlated bond rotations for C(alpha)H fluctuations. Motional parameters for NH groups are more structurally correlated, with NH order parameters, for example, being larger for residues in more structured regions of beta-sheet and helix and generally smaller for residues in the loop and turns. This is most likely related to the observation that NH order parameters are correlated to hydrogen bonding. This study contributes to the general understanding of protein dynamics and exemplifies an alternative and easier way to analyze NMR relaxation data.     

甘薯品种营养成份与抗小象虫的相关性研究

通过田间和网室测定结果,抗小象虫较好的甘薯品种有抗虫1号、台农26、Tis2534、Ricin和鸡蛋黄;抗小象虫较弱的品种有新种花、惠红早、“329”、广薯15等。甘薯品种的营养成份与抗小象虫相关性分析结果表明,抗、感品种与粗纤维、粗脂肪含量无明显相关,与粗淀粉有显负相关,R1=-0．9935,而与粗蛋白和18种氨基酸总量有显正相关,R2=0．9741,R3=0．9621。表现粗淀粉含量高的品种,其虫害指敦较低,抗虫性强;而粗蛋白含量和18种氨基酸总量高的品种,其虫害指数较高,抗虫性则表现较弱。测定分析说明了甘薯品种营养成份与抗虫性存在一定的相关性。     

Heat capacities and a snapshot of the energy landscape in protein GB1 from the pre-denaturation temperature dependence of backbone NH nanosecond fluctuations

Protein stability is usually characterized calorimetrically by a melting temperature and related thermodynamic parameters. Despite its importance, the microscopic origin of the melting transition and the relationship between thermodynamic stability and dynamics remains a mystery. Here, NMR relaxation parameters were acquired for backbone 15NH groups of the 56 residue immunoglobulin-binding domain of streptococcal protein G over a pre-denaturation temperature range of 5-50 degrees C. Relaxation data were analyzed using three methods: the standard three-Lorentzian model free approach; the F(omega)=2omegaJ(omega) spectral density approach that yields motional correlation time distributions, and a new approach that determines frequency-dependent order parameters. Regardless of the method of analysis, the temperature dependence of internal motional correlation times and order parameters is essentially the same. Nanosecond time-scale internal motions are found for all NHs in the protein, and their temperature dependence yields activation energies ranging up to about 33kJ/mol residue. NH motional barrier heights are structurally correlated, with the largest energy barriers being found for residues in the most "rigid" segments of the fold: beta-strands 1 and 4 and the alpha-helix. Trends in this landscape also parallel the free energy of folding-unfolding derived from hydrogen-deuterium (H-D) exchange measurements, indicating that the energetics for internal motions occurring on the nanosecond time-scale mirror those occurring on the much slower time-scale of H-D exchange. Residual heat capacities, derived from the temperature dependence of order parameters, range from near zero to near 100J/mol K residue and correlate with this energy landscape. These results provide a unique picture of this protein's energy landscape and a relationship between thermodynamic stability and dynamics that suggests thermosensitive regions in the fold that could initiate the melting process.     

The devil in the details of life-history evolution: Instability and reversal of genetic correlations during selection on<Emphasis Type="Italic">Drosophila</Emphasis> development

The evolutionary relationships between three major components of Darwinian fitness, development rate, growth rate and preadult survival, were estimated using a comparison of 55 distinct populations ofDrosophila melanogaster variously selected for age-specific fertility, environmental-stress tolerance and accelerated development. Development rate displayed a strong net negative evolutionary correlation with weight at eclosion across all selection treatments, consistent with the existence of a size-versus-time tradeoff between these characters. However, within the data set, the magnitude of the evolutionary correlation depended upon the particular selection treatments contrasted. A previously proposed tradeoff between preadult viability and growth rate was apparent only under weak selection for juvenile fitness components. Direct selection for rapid development led to sharp reductions in both growth rates and viability. These data add to the mounting results from experimental evolution that illustrate the sensitivity of evolutionary correlations to (i) genotype-by-environment (G X E) interaction, (ii) complex functional-trait interactions, and (iii) character definition. Instability, disappearance and reversal of patterns of genetic covariation often occur over short evolutionary time frames and as the direct product of selection, rather than some stochastic process. We suggest that the functional architecture of fitness is a rapidly evolving matrix with reticulate properties, a matrix that we understand only poorly.     

Measuring mast seeding behavior: relationships among population variation,individual variation and synchrony

Mast seeding, or masting, is the variable production of flowers, seeds, or fruit across years more or less synchronously by individuals within a population. A critical issue is the extent to which temporal variation in seed production over a collection of individuals can be viewed as arising from a combination of individual variation and synchrony among individuals. Studies of masting typically quantify such variation in terms of the coefficient of variation (CV). In this paper we examine mathematically how the population CV relates to the mean individual CV and synchrony, concluding that the relationship is a complex one which cannot isolate an overall measure of synchrony, and involves additional factors, principally the number of plants sampled and the mean productivity per plant. Our development suggests some simple approximate relationships of population CV to individual variability, synchrony and the number of individuals. These were found to fit quite well when applied to data from 59 studies which included seed production at the individual level.     

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.