Genetic and environmental sources of covariance between reading tests used in neuropsychological assessment and IQ subtests

In this study, we examined genetic and environmental influences on covariation among two reading tests used in neuropsychological assessment (Cambridge Contextual Reading Test [CCRT], [Beardsall, L., and Huppert, F. A. ( 1994). J. Clin. Exp. Neuropsychol. 16: 232 - 242], Schonell Graded Word Reading Test [SGWRT], [ Schonell, F. J., and Schonell, P. E. ( 1960). Diagnostic and attainment testing. Edinburgh: Oliver and Boyd.]) and among a selection of IQ subtests from the Multidimensional Aptitude Battery (MAB), [Jackson, D. N. (1984). Multidimensional aptitude battery, Ontario: Research Psychologists Press.] and the Wechsler Adult Intelligence Scale-Revised (WAIS-R) [Wechsler, D. (1981). Manual for the Wechsler Adult Intelligence Scale-Revised (WAIS-R). San Antonio: The Psychological Corporation]. Participants were 225 monozygotic and 275 dizygotic twin pairs aged from 15 years to 18 years ( mean, 16 years). For Verbal IQ subtests, phenotypic correlations with the reading tests ranged from 0.44 to 0.65. For Performance IQ subtests, phenotypic correlations with the reading tests ranged from 0.23 to 0.34. Results of Structural Equation Modeling (SEM) supported a model with one genetic General factor and three genetic group factors ( Verbal, Performance, Reading). Reading performance was influenced by the genetic General factor ( accounting for 13% and 20% of the variance for the CCRT and SGWRT, respectively), the genetic Verbal factor ( explaining 17% and 19% of variance for the CCRT and SGWRT), and the genetic Reading factor ( explaining 21% of the variance for both the CCRT and SGWRT). A common environment factor accounted for 25% and 14% of the CCRT and SGWRT variance, respectively. Genetic influences accounted for more than half of the phenotypic covariance between the reading tests and each of the IQ subtests. The heritabilities of the CCRT and SGWRT were 0.54 and 0.65, respectively. Observable covariance between reading assessments used by neuropsychologists to estimate IQ and IQ subtests appears to be largely due to genetic effects.

Collaborative decision-making processes for maintaining biodiversity: Two Australian case studies

There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

An investigation into effects of long-distance seed dispersal on organelle population genetic structure and colonization rate: a model analysis

A simulation-based modelling approach is used to examine the effects of stratified seed dispersal (representing the distribution of the majority of dispersal around the maternal parent and also rare long-distance dispersal) on the genetic structure of maternally inherited genomes and the colonization rate of expanding plant populations. The model is parameterized to approximate postglacial oak colonization in the UK, but is relevant to plant populations that exhibit stratified seed dispersal. The modelling approach considers the colonization of individual plants over a large area (three 500 km x 10 km rolled transects are used to approximate a 500 km x 300 km area). Our approach shows how the interaction of plant population dynamics with stratified dispersal can result in a spatially patchy haplotype structure. We show that while both colonization speeds and the resulting genetic structure are influenced by the characteristics of the dispersal kernel, they are robust to changes in the periodicity of long-distance events, provided the average number of long-distance dispersal events remains constant. We also consider the effects of additional physical and environmental mechanisms on plant colonization. Results show significant changes in genetic structure when the initial colonization of different haplotypes is staggered over time and when a barrier to colonization is introduced. Environmental influences on survivorship and fecundity affect both the genetic structure and the speed of colonization. The importance of these mechanisms in relation to the postglacial spread and genetic structure of oak in the UK is discussed.

Adaptation to being at-risk for Huntington's disease and the availability of genetic testing: Application of a stress and coping model

This study examined the utility of a stress/coping model in explaining adaptation in two groups of people at-risk for Huntington's Disease (HD): those who have not approached genetic testing services (non-testees) and those who have engaged a testing service (testees). The aims were (1) to compare testees and non-testees on stress/coping variables, (2) to examine relations between adjustment and the stress/coping predictors in the two groups, and (3) to examine relations between the stress/coping variables and testees' satisfaction with their first counselling session. Participants were 44 testees and 40 non-testees who completed questionnaires which measured the stress/coping variables: adjustment (global distress, depression, health anxiety, social and dyadic adjustment), genetic testing concerns, testing context (HD contact, experience, knowledge), appraisal (control, threat, self-efficacy), coping strategies (avoidance, self-blame, wishful thinking, seeking support, problem solving), social support and locus of control. Testees also completed a genetic counselling session satisfaction scale. As expected, non-testees reported lower self-efficacy and control appraisals, higher threat and passive avoidant coping than testees. Overall, results supported the hypothesis that within each group poorer adjustment would be related to higher genetic testing concerns, contact with HD, threat appraisals, passive avoidant coping and external locus of control, and lower levels of positive experiences with HD, social support, internal locus of control, self-efficacy, control appraisals, problem solving, emotional approach and seeking social support coping. Session satisfaction scores were positively correlated with dyadic adjustment, problem solving and positive experience with HD, and inversely related to testing concerns, and threat and control appraisals. Findings support the utility of the stress/coping model in explaining adaptation in people who have decided not to seek genetic testing for HD and those who have decided to engage a genetic testing service.

A genetic two-factor model of the covariation among a subset of Multidimensional Aptitude Battery and Wechsler Adult Intelligence Scale - Revised subtests

The phenotypic and genetic factor structure of performance on five Multidimensional Aptitude Battery (MAB) subtests and one Wechsler Adult Intelligence Scale-Revised (WAIS-R) subtest was explored in 390 adolescent twin pairs (184 monozygotic [MZ]; 206 dizygotic (DZ)). The temporal stability of these measures was derived from a subsample of 49 twin pairs, with test-retest correlations ranging from .67 to .85. A phenotypic factor model, in which performance and verbal factors were correlated, provided a good fit to the data. Genetic modeling was based on the phenotypic factor structure, but also took into account the additive genetic (A), common environmental (C), and unique environmental (E) parameters derived from a fully saturated ACE model. The best fitting model was characterized by a genetic correlated two-factor structure with specific effects, a general common environmental factor, and overlapping unique environmental effects. Results are compared to multivariate genetic models reported in children and adults, with the most notable difference being the growing importance of common genes influencing diverse abilities in adolescence. (C) 2003 Elsevier Inc. All rights reserved.

A genetic investigation of the covariation among Inspection Time, Choice Reaction Time, and IQ subtest scores

Information processing speed, as measured by elementary cognitive tasks, is correlated with higher order cognitive ability so that increased speed relates to improved cognitive performance. The question of whether the genetic variation in Inspection Time (IT) and Choice Reaction Time (CRT) is associated with IQ through a unitary factor was addressed in this multivariate genetic study of IT, CRT, and IQ subtest scores. The sample included 184 MZ and 206 DZ twin pairs with a mean age of 16.2 years (range 15-18 years). They were administered a visual (pi-figure) IT task, a two-choice RT task, five computerized subtests of the Multidimensional Aptitude Battery, and the digit symbol substitution subtest from the WAIS-R. The data supported a factor model comprising a general, three group (verbal ability, visuospatial ability, broad speediness), and specific genetic factor structure, a shared environmental factor influencing all tests but IT, plus unique environmental factors that were largely specific to individual measures. The general genetic factor displayed factor loadings ranging between 0.35 and 0.66 for the IQ subtests, with IT and CRT loadings of -0.47 and -0.24, respectively. Results indicate that a unitary factor is insufficient to describe the entire relationship between cognitive speed measures and all IQ subtests, with independent genetic effects explaining further covariation between processing speed (especially CRT) and Digit Symbol.

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

Determining the effective dimensionality of the genetic variance-covariance matrix

Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by AMEMIYA (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In, contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery.

Genetic manipulation of blood group carbohydrates alters development and pathfinding of primary sensory axons of the olfactory systems

Primary sensory neurons in the vertebrate olfactory systems are characterised by the differential expression of distinct cell surface carbohydrates. We show here that the histo-blood group H carbohydrate is expressed by primary sensory neurons in both the main and accessory olfactory systems while the blood group A carbohydrate is expressed by a subset of vomeronasal neurons in the developing accessory olfactory system. We have used both loss-of-function and gain-of-function approaches to manipulate expression of these carbohydrates in the olfactory system. In null mutant mice lacking the alpha(1,2)fucosyltransferase FUT1, the absence of blood group H carbohydrate resulted in the delayed maturation of the glomerular layer of the main olfactory bulb. In addition, ubiquitous expression of blood group A on olfactory axons in gain-of-function transgenic mice caused mis-routing of axons in the glomerular layer of the main olfactory bulb and led to exuberant growth of vomeronasal axons in the accessory olfactory bulb. These results provide in vivo evidence for a role of specific cell surface carbohydrates during development of the olfactory nerve pathways. (c) 2006 Elsevier Inc. All rights reserved.

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Genetic and Cultural Transmission of Smoking Initiation: An Extended Twin Kinship Model

Background Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a significant role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent–offspring transmission and their contribution to the variability explained by genetic and/or environmental factors. Methods We examined the role of genetic and environmental factors for smoking initiation using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission. A dichotomous lifetime smoking measure was obtained from twins and relatives in the Virginia 30,000 sample. Results Results demonstrate that both genetic and environmental factors play a significant role in the liability to smoking initiation. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission and resulting genotype–environment covariance. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent–offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (i) age × gene interaction, and (ii) social homogamy. Neither mechanism provided a significantly better explanation of the data, although age regression was significant. Conclusions This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on smoking initiation.