What life cycle graphs can tell about the evolution of life histories

We analyze long-term evolutionary dynamics in a large class of life history models. The model family is characterized by discrete-time population dynamics and a finite number of individual states such that the life cycle can be described in terms of a population projection matrix. We allow an arbitrary number of demographic parameters to be subject to density-dependent population regulation and two or more demographic parameters to be subject to evolutionary change. Our aim is to identify structural features of life cycles and modes of population regulation that correspond to specific evolutionary dynamics. Our derivations are based on a fitness proxy that is an algebraically simple function of loops within the life cycle. This allows us to phrase the results in terms of properties of such loops which are readily interpreted biologically. The following results could be obtained. First, we give sufficient conditions for the existence of optimisation principles in models with an arbitrary number of evolving traits. These models are then classified with respect to their appropriate optimisation principle. Second, under the assumption of just two evolving traits we identify structural features of the life cycle that determine whether equilibria of the monomorphic adaptive dynamics (evolutionarily singular points) correspond to fitness minima or maxima. Third, for one class of frequency-dependent models, where optimisation is not possible, we present sufficient conditions that allow classifying singular points in terms of the curvature of the trade-off curve. Throughout the article we illustrate the utility of our framework with a variety of examples.     

Interrelationships of Staphyliniform groups inferred from 18S and 28S rDNA sequences, with special emphasis on Hydrophiloidea (Coleoptera, Staphyliniformia)

The series Staphyliniformia is one of the mega‐diverse groups of Coleoptera, but the relationships among the main families are still poorly understood. In this paper we address the interrelationships of staphyliniform groups, with special emphasis on Hydrophiloidea and Hydraenidae, based on partial sequences of the ribosomal genes 18S rDNA and 28S rDNA. Sequence data were analysed with parsimony and Bayesian posterior probabilities, in an attempt to overcome the likely effect of some branches longer than the 95% cumulative probability of the estimated normal distribution of the path lengths of the species. The inter‐family relationships in the trees obtained with both methods were in general poorly supported, although most of the results based on the sequence data are in good agreement with morphological studies. In none of our analyses a close relationship between Hydraenidae and Hydrophiloidea was supported, contrary to the traditional view but in agreement with recent morphological investigations. Hydraenidae form a clade with Ptiliidae and Scydmaenidae in the tree obtained with Bayesian probabilities, but are placed as basal group of Staphyliniformia (with Silphidae as subordinate group) in the parsimony tree. Based on the analysed data with a limited set of outgroups Scarabaeoidea are nested within Staphyliniformia. However, this needs further support. Hydrophiloidea s.str., Sphaeridiinae, Histeroidea (Histeridae + Sphaeritidae), and all staphylinoid families included are confirmed as monophyletic, with the exception of Hydraenidae in the parsimony tree. Spercheidae are not a basal group within Hydrophiloidea, as has been previously suggested, but included in a polytomy with other Hydrophilidae in the Bayesian analyses, or its sistergroup (with the inclusion of Epimetopidae) in the parsimony tree. Helophorus is placed at the base of Hydrophiloidea in the parsimony tree. The monophyly of Hydrophiloidea s.l. (including the histeroid families) and Staphylinoidea could not be confirmed by the analysed data. Some results, such as a placement of Silphidae as subordinate group of Hydraenidae (parsimony tree), or a sistergroup relationship between Ptiliidae and Scydmaenidae, appear unlikely from a morphological point of view.     

Demonstration of choleragen-dependent ADP-ribosylation in whole cells and correlation with the activation of adenylate cyclase

3T3C₂ mouse fibroblasts rendered permeable to (α^?32P)NAD⁺ show cholera toxin-dependent labeling of a 45,000 m.w. protein and of a doublet of polypeptides around 52,000 m.w. These same bands are ADP-ribosylated in broken cells. Membranes prepared from pigeon erythrocytes pretreated with choleragen show a decrease in subsequent cholera toxin-specific ADP-ribosylation of a 43,000 m.w. polypeptide. Both whole cell and broken cell adenylate cyclase activation and toxin-specific ADP-ribosylation are reversed specifically by low pH and high concentrations of toxin and nicotinamide in all systems. Thus ADP-ribosylation appears to be relevant to the molecular action of choleragen in whole cells as well as in broken cells.     

Enzyme-coding genes as molecular clocks: The molecular evolution of animal alpha-amylases

Summary We constructed a cDNA library for the beetle,Tribolium castaneum. This library was screened using a cloned amylase gene fromDrosophila melanogaster as a molecular probe. Beetle amylase cDNA clones were isolated from this bank, and the nucleotide sequence was obtained for a cDNA clone with a coding capacity for 228 amino acids. Both the nucleotide sequence and predicted amino acid sequence were compared to our recent results forD. melanogaster alpha-amylases, along with published sequences for other alpha-amylases. The results show that animal alpha-amylases are highly conserved over their entire length. A borader comparison, which includes plant and microbial alpha-amylase sequences, indicates that parts of the gene are conserved between prokaryotes, plants, and animals. We discuss the potential importance of this and other enzyme-coding genes for the construction of molecular phylogenies and for the study of the general question of molecular clocks in evolution.     

Correlates and predictors of the age of menarche

In a cross-sectional study of 452 girls between 10 and 16 years of age 36 indices of physical and 50 of mental development were tested for their correlation with age at menarche and chronological age, as well as for their predictive power for estimating menarche by multiple regression analysis. Indices of physical maturity and body weight when adjusted for chronological age showed the highest partial correlation coefficients with age at menarche. Among mental characters which show lower intercorrelations with menarche occurred the highest correlation coefficients for a handmotor factor "Spurennachzeichnen" and a factor "Gruppenabh?ngigkeit" (which indicates a type of social motivation). In general physical and mental factors correlate higher with chronological age than with age at menarche. By multiple regression analysis we determined 14 physical and 25 mental predictors explaining 21% and 17% respectively of the variance of age at menarche. The error of the estimate predicting menarche on body weight without knowledge of onset of menarche is +/- 1 year. Using chronological age in a sample of girls before menarche the error of the estimate only is +/- 6 months. To compare the predictive power of chronological age combined with body weight or with skeletal age the time interval is calculated within which 95% of girls attain menarche. The range of prediction extends from 4.3 to 1 year on chronological age (11-16 years); using mean body weight it can be improved by 1.8 to 6 months, while using mean skeletal age an improvement of 0.2 to 3.9 months is possible compared with body weight. The correlations between age at menarche and physical and mental variables are attributed to a common hormonal influence on rate of development.     

Biochemical characterization of chromatin fractions isolated from induced and uninduced friend erythroleukemia cells

Summary Chromatin fractions from Friend erythroleukemia cells after induction of differentiation by dimethylsulfoxide (DMSO) were compared in their biochemical characteristics to fractions from uninduced cells. Fractions were prepared by extracting chromatin from nuclei after mild micrococcal nuclease treatment with increasing concentrations of NaCl according to Sanders [1]. This procedure has been found to release chromatin containing hyperacetylated histones preferentially [2]. The fractions obtained by this procedure were analysed in respect to the amount of chromatin released, the amount of histone H1, the degree of acetylation of histone H4, the presence of non-histone proteins and the concentration of transcribed and non-transcribed sequences. It was found that the fractions differ in the amount of histone H1 present, in several non-histone proteins and in the acetylation of histonie H4, regardless whether induced or uninduced cells were analysed. The distribution of transcribed sequences versus non-transcribed sequences among the fractions was the same, demonstrating that this fractionation procedure, although leading to fractions with biochemical differences, is not able to discriminate functional states of chromatin and that the biochemical characteristics of the fractions may be common to both, active as well as inactive states of chromatin.