Ionizing radiation and genetic risks VII. The concept of mutation component and its use in risk estimation for Mendelian diseases

The responsiveness of Mendelian diseases to an increase in the mutation rate is studied by using the concept of the mutation component (MC) of genetic diseases. Algebraic expressions to evaluate MC at any specific generation following either a one-time or a permanent increase in mutation rate are derived and are illustrated with numerical examples. For a one-time increase in mutation rate, the analysis shows that the first generation MC for autosomal dominant diseases is equal to the selection coefficient; this is also true for X-linked diseases (adjusted for the proportion of X-chromosomes in males). For autosomal recessive diseases the first generation MC is substantially smaller than that for autosomal dominants. In subsequent generations MC gradually decays to zero. Under conditions of a permanent increase in the mutation rate, the MC for autosomal dominant, X-linked and completely recessive autosomal disorders progressively increases to reach a value of one at the new equilibrium. For incompletely recessive autosomal disorders, however, the MC at equilibrium can be larger than one. The rates of approach to the new equilibrium are different for the different classes of diseases, dictated by selection and time (in generations) following radiation exposure. The effects of increases in mutation rate on MC are more pronounced for autosomal dominants, followed by X-linked and are far less for autosomal recessives. Even for autosomal dominants, the early generation effects of radiation exposures would not be appreciable unless the heterozygotes have a severely reduced fitness.     

Quantitative analysis of correlations among flower traits in Gerbera hybrida, Compositae. III. Genetic variability and structure of principal component traits

 A sample of 36 flower traits consisting of six morphological categories in the Davis population of gerbera was restructured into phenotypic and genetic principal component traits. The first 5 phenotypic principal component traits accounted for 62% of the total phenotypic variance of the 36 traits and have moderate to high heritablities. The first 5 genetic principal component traits account for 97% of total genetic variance and all have high heritability. Morphological structure of these component traits suggest an underlying process identified by the first genetic principal component involving largely trans and disk floret traits. The results of this study indicate that the quantitative genetic structure of the gerbera flower is controlled by a few independent components and that principal component analysis is a useful tool to reveal variation in this structure. These composite traits are heritable and are expected to respond to selection. Received: 20 September 1997 / Accepted: 19 January 1998     

Modelling the species richness distribution of French dung beetles (Coleoptera, Scarabaeidae) and delimiting the predictive capacity of different groups of explanatory variables

Aim To predict French Scarabaeidae dung beetle species richness distribution, and to determine the possible underlying causal factors. Location The entire French territory has been studied by dividing it into 301 grid cells of 0.72 × 0.36 degrees. Method Species richness distribution was predicted using generalized linear models to relate the number of species with spatial, topographic and climate variables in grid squares previously identified as well sampled (n = 66). The predictive function includes the curvilinear relationship between variables, interaction terms and the significant third‐degree polynomial terms of latitude and longitude. The final model was validated by a jack‐knife procedure. The underlying causal factors were investigated by partial regression analysis, decomposing the variation in species richness among spatial, topographic and climate type variables. Results The final model accounts for 86.2% of total deviance, with a mean jack‐knife predictive error of 17.7%. The species richness map obtained highlights the Mediterranean as the region richest in species, and the less well‐explored south‐western region as also being species‐rich. The largest fraction of variability (38%) in the number of species is accounted for by the combined effect of the three groups of explanatory variables. The spatially structured climate component explains 21% of variation, while the pure climate and pure spatial components explain 14% and 11%, respectively. The effect of topography was negligible. Conclusions Delimiting the adequately inventoried areas and elaborating forecasting models using simple environmental variables can rapidly produce an estimate of the species richness distribution. Scarabaeidae species richness distribution seems to be mainly influenced by temperature. Minimum mean temperature is the most influential variable on a local scale, while maximum and mean temperature are the most important spatially structured variables. We suggest that species richness variation is mainly conditioned by the failure of many species to go beyond determined temperature range limits.     

Ecomorphological study of large canids from the lower Pleistocene of southeastern Spain

An ecomorphological analysis of the skeletal remains of large canids, Canis (Xenocyon) falconeri and Canis etruscus (Mammalia, Carnivora, Canidae), preserved in an assemblage of large mammals from the lower Pleistocene site at Venta Micena (Guadix–Baza Basin, Orce, Granada, southeastern Spain) is reported. Mean body mass of adult individuals was estimated to be around 10 kg for C. etruscus and approximately 28 kg for C. falconeri using multiple regression. A comparative study of tooth measurements in modem canids, using principal components and discriminant function analysis, infers quite different ecomorphological adaptations and feeding behavior for both fossil species. The craniodental morphology of C. falconeri is similar to that shown by extant hypercarnivorous canids whose diet include more than 70% of vertebrate meat, whereas C. etruscus shows a cranial morphology similar to those of modem omnivorous species, thus indicating a dietary niche in which vertebrate meat represented less than 70% of its diet, with other feeding resources making up the balance. These results suggest that there was a marked ecological segregation between both sympatric species of large canids. The find of a complete skull of C. falconeri showing bilateral asymmetry and marked dental anomalies could suggest high levels of genetic homozygosis in the population which inhabited this region during early Pleistocene times, possibly as a consequence of isolation and the low number of individuals. This may have subsequently led to the extinction of C. falconeri in the Western fringe of Europe. The survival of this pathological individual to adulthood indicates that this species may have developed cooperative behavior similar to that of modem African wild dogs.     

Differentiation of Three Varieties of Rhizoctonia circinata; var. circinata, var. oryzae and var. zeae on the Basis of Cellular Fatty Acid Composition

Cellular fatty acid analysis was employed to differentiate three varieties of Rhizoctonia circinata ; var. circinata , var. oryzae and var. zeae . Eight fatty acids including myristic (14 : 0), pentadecanoic (15 : 0), palmitic (16 : 0), palmitoleic (16 : 1  cis 9), stearic (18 : 0), oleic (18 : 1  cis 9), linoleic (18 : 2  cis 9,12) and linolenic (18 : 3  cis 9,12) acids were present in isolates of all three varieties of R. circinata . Heptadecanoic acid (17 : 0) was detected in isolates of R. circinata var. zeae but not in isolates of R. circinata var. circinata or R. circinata var. oryzae . Palmitic, oleic and linoleic acids were the major fatty acids found, comprising 94–98% of the whole-cell fatty acid content. The remaining fatty acids were present in small amounts. Based on the composition (%) of fatty acids, isolates of R. circinata var. circinata , R. circinata var. oryzae and R. circinata var. zeae were clearly differentiated into three groups as shown by principal component and cluster analyses. This finding agrees well with the grouping of R. circinata into three varieties based on differences in colony morphology of the vegetative state. In principal component and cluster analysis, isolates of R. circinata var. circinata from Japan and Alaska were indistinguishable.     

Improved endocervical sampling and HPV viral load detection by Cervex-Brush® Combi

OBJECTIVE: Liquid-based cytology (LBC) for cervical screening is becoming increasingly used. Together with SurePath LBC, various collecting devices can be utilized, among which the Cervex-Brush is the most widely used. The new Rovers Cervex-Brush Combi combines the advantages of the Cervex-Brush with the EndoCervex-Brush increasing sampling of the endocervical canal. The objective of this study was to analyse and to compare the Cervex-Brush Combi with the Cervex-Brush for the collection of squamous and endocervical cells, human papillomavirus (HPV) typing/quantification and disease detection in SurePath LBC. METHODS: Using either the Cervex-Brush or the Cervex-Brush Combi 100 consecutive SurePath LBC samples were collected using each brush type. All 200 slides were read by the FocalPoint and screened by guided screening using slide wizards. The viral load of HPV type 16 E7, 18 E7, 31 E6, 33 L1, 33 E6, 35 E4, 39 E7, 45 E7, 51 E6, 52 L1, 52 E7, 53 E6, 56 E7, 58 L1, 58 E6, 59 E7, 66 E6 and 68 E7 was determined using a TaqMan-based real-time quantitative PCR analysis. RESULTS: The mean number of sampled squamous cells did not differ between the two brush types (54 963 versus 54 595 cells). The use of the Cervex-Brush Combi, however, resulted in a two- to threefold increase in the number of sampled endocervical cells (P < 0.00001). Using the Cervex-Brush Combi slightly more lesions were detected (three versus two low-grade squamous intraepithelial lesions), and resulted in the detection of more atypical squamous cells of undetermined significance (six versus three). In the Cervex-Brush group, 60% (3/5) of abnormal smears were positive for oncogenic HPV types, whereas 66.7% (6/9) of abnormal smears in the Cervex-Brush Combi group tested positive. The median HPV viral load for samples taken with the Cervex-Brush Combi was 0.1825 copies/cell and was significantly higher than in samples taken with the Cervex-Brush (0.0042 copies/cell) (P = 0.02). CONCLUSION: Sampling with the Cervex-Brush Combi resulted in the collection of the same amount of squamous cells, but in a two to threefold harvest of endocervical cells. This led to the detection of a higher viral load for oncogenic HPV and an increase in the number of detected abnormal smears.     

MEASURING SELECTION AND CONSTRAINT IN THE EVOLUTION OF GROWTH

We present a quantitative genetic model for the evolution of growth trajectories that makes no assumptions about the shapes of growth trajectories that are possible. Evolution of a population's mean growth trajectory is governed by the selection gradient function and the additive genetic covariance function. The selection gradient function is determined by the impact of changes in size on the birth and death rates at different ages, and can be estimated for natural populations. The additive genetic covariance function can also be estimated empirically, as we demonstrate with four vertebrate populations. Using the genetic data from mice, a computer simulation shows that evolution of a growth trajectory can be constrained by the absence of genetic variation for certain changes in the trajectory's shape. These constraints can be visualized with an analysis of the covariance function. Results from four vertebrate populations show that while each has substantial genetic variation for some evolutionary changes in its growth trajectory, most types of changes have little or no variation available. This suggests that constraints may often play an important role in the evolution of growth.     

THE MIXED-MODEL ANALYSIS OF VARIANCE APPLIED TO QUANTITATIVE GENETICS: BIOLOGICAL MEANING OF THE PARAMETERS

The mixed-model factorial analysis of variance has been used in many recent studies in evolutionary quantitative genetics. Two competing formulations of the mixed-model ANOVA are commonly used, the “Scheffe” model and the “SAS” model; these models differ in both their assumptions and in the way in which variance components due to the main effect of random factors are defined. The biological meanings of the two variance component definitions have often been unappreciated, however. A full understanding of these meanings leads to the conclusion that the mixed-model ANOVA could have been used to much greater effect by many recent authors. The variance component due to the random main effect under the two-way SAS model is the covariance in true means associated with a level of the random factor (e.g., families) across levels of the fixed factor (e.g., environments). Therefore the SAS model has a natural application for estimating the genetic correlation between a character expressed in different environments and testing whether it differs from zero. The variance component due to the random main effect under the two-way Scheffe model is the variance in marginal means (i.e., means over levels of the fixed factor) among levels of the random factor. Therefore the Scheffe model has a natural application for estimating genetic variances and heritabilities in populations using a defined mixture of environments. Procedures and assumptions necessary for these applications of the models are discussed. While exact significance tests under the SAS model require balanced data and the assumptions that family effects are normally distributed with equal variances in the different environments, the model can be useful even when these conditions are not met (e.g., for providing an unbiased estimate of the across-environment genetic covariance). Contrary to statements in a recent paper, exact significance tests regarding the variance in marginal means as well as unbiased estimates can be readily obtained from unbalanced designs with no restrictive assumptions about the distributions or variance-covariance structure of family effects.