Does chemical composition of individual Scots pine trees determine the biodiversity of their associated ground vegetation?

Despite plant secondary metabolites being major determinants of species interactions and ecosystem processes, their role in the maintenance of biodiversity has received little attention. In order to investigate the relationship between chemical and biological diversity in a natural ecosystem, we considered the impact of chemical diversity in individual Scots pine trees (Pinus sylvestris) on species richness of associated ground vegetation. Scots pine trees show substantial genetically determined constitutive variation between individuals in concentrations of a group of secondary metabolites, the monoterpenes. When the monoterpenes of particular trees were assessed individually, there was no relationship with species richness of associated ground flora. However, the chemical diversity of monoterpenes of individual trees was significantly positively associated with the species richness of the ground vegetation beneath each tree, mainly the result of an effect among the non‐woody vascular plants. This correlation suggests that the chemical diversity of the ecosystem dominant species has an important role in shaping the biodiversity of the associated plant community. The extent and significance of this effect, and its underlying processes require further investigation.     

Immunoglobulin G genotypes and the risk of schizophrenia

Genes of the immune system are relevant to the etiology of schizophrenia. However, to our knowledge, no large-scale studies, using molecular methods, have been undertaken to investigate the role of highly polymorphic immunoglobulin GM (γ marker) genes in this disorder. In this investigation, we aimed to determine whether particular GM genotypes were associated with susceptibility to schizophrenia. Using a matched case–control study design, we analyzed DNA samples from 798 subjects—398 patients with schizophrenia and 400 controls—obtained from the U.S. National Institute of Mental Health Repository. GM alleles were determined by the TaqMan^® genotyping assay. The GM 3/3; 23?/23? genotype was highly significantly associated with susceptibility to schizophrenia (p = 0.0002). Subjects with this genotype were over three times (OR 3.4; 95 % CI 1.7–6.7) as likely to develop schizophrenia as those without this genotype. Our results show that immunoglobulin GM genes are risk factors for the development of schizophrenia. Since GM alleles have been implicated in gluten sensitivity and in immunity to neurotropic viruses associated with cognitive impairment, the results presented here may help unify these two disparate areas of pathology affected in this disorder.     

Extensions to pedigree analysis I. Likehood calculations for simple and complex pedigrees.

A graph theoretic definition of pedigrees is given and a distinction drawn between simple and complex pedigrees. Algorithms are presented to calculate the likeihood of any kind of pedigree, assuming only segregation at a finite set of loci, nonassortative mating and no environmental correlations; multiple births and consanguineous marriages are explicity allowed for. The formulation given can lead to more powerful genetic counselling, segregation analysis and linkage analysis.     

Biometrical Genetics with One or Two Loci: The Inheritance of Physiological Characters in Mice

Maximum likelihood methods have been used to compare the fit of twenty different genetic models to experimental data on fourteen characters, each measured on two parental strains, F(1) hybrids and both backcrosses. Although variation in all characters was continuous, differentiation between the various models was meaningful, the mean likelihood ratio between the best and worst models for each character being greater than 10(4). Models with only one or two loci were adequate to account for the observed genetic variation in eleven of the fourteen characters. These results indicate that even in species without special genetic advantages, it may be possible to identify individually some of the genes responsible for naturally-occurring variation within the range of normality.     

The Analysis of Quantitative Traits for Simple Genetic Models from Parental, F1 and Backcross Data

THE FOLLOWING MODELS ARE CONSIDERED FOR THE GENETIC DETERMINATION OF QUANTITATIVE TRAITS: segregation at one locus, at two linked loci, at any number of equal and additive unlinked loci, and at one major locus and an indefinite number of equal and additive loci. In each case an appropriate likelihood is given for data on parental, F(1) and backcross individuals, assuming that the environmental variation is normally distributed. Methods of testing and comparing the various models are presented, and methods are suggested for the simultaneous analysis of two or more traits.     

The liver/erythrocyte pyruvate kinase gene complex [Pk-1] in the mouse: regulatory gene mutations.

Nine enzyme activity variants and one charge variant of liver/erythrocyte pyruvate kinase have been found amongst laboratory and wild mice. Four of the enzyme activity variants were previously reported to be caused by allelic differences in the structural gene, Pk-1s. Analysis of two putative regulatory gene mutations is now reported, both of which map at, or close to, the structural gene on chromosome 3. One of these mutations, in the inbred strain SWR, is tissue specific, affecting enzyme concentration in the liver but not the erythrocyte the other, which arose in a mutation experiment, doubles the enzyme concentration in both tissues. The organization and the nomenclature in the [Pk-1] gene complex are discussed and are compared with the organization of other comprehensively analysed gene complexes in the mouse.     

MULTISITE MARK-RECAPTURE FOR CETACEANS: POPULATION ESTIMATES WITH BAYESIAN MODEL AVERAGING

Mark-recapture techniques are widely used to estimate the size of wildlife populations. However, in cetacean photo-identification studies, it is often impractical to sample across the entire range of the population. Consequently, negatively biased population estimates can result when large portions of a population are unavailable for photographic capture. To overcome this problem, we propose that individuals be sampled from a number of discrete sites located throughout the population's range. The recapture of individuals between sites can then be presented in a simple contingency table, where the cells refer to discrete categories formed by combinations of the study sites. We present a Bayesian framework for fitting a suite of log-linear models to these data, with each model representing a different hypothesis about dependence between sites. Modeling dependence facilitates the analysis of opportunistic photo-identification data from study sites located due to convenience rather than by design. Because inference about population size is sensitive to model choice, we use Bayesian Markov chain Monte Carlo approaches to estimate posterior model probabilities, and base inference on a model-averaged estimate of population size. We demonstrate this method in the analysis of photographic mark-recapture data for bottlenose dolphins from three coastal sites around NE Scotland.