Genetic and Other Contributions to Alcohol Intake in Rhesus Macaques ( Macaca mulatta )

The etiology of alcoholism and alcohol abuse, like many other complex diseases, is heterogeneous and multifactorial. Numerous studies demonstrate a genetic contribution to variation in the expression of alcohol-related disorders in humans. Over the past decade, nonhuman primates have emerged as a valuable model for some aspects of human alcohol abuse because of their phylogenetic proximity to humans. Long-term, longitudinal studies of rhesus macaques ( Macaca mulatta ) have provided much insight into environmental influences, especially early life experiences, on alcohol consumption and behavior patterns that characterize alcohol intake later in life. It is not known, however, whether there is a genetic component as well to the variation seen in alcohol consumption in rhesus macaques. A significant genetic component to variation in alcohol consumption in rhesus macaques would show for the first time that like humans, for nonhuman primates additive genetic influences are important. Moreover, their use as a model for alcohol-related disorders in humans would have even greater relevance and utility for designing experiments incorporating the expanding molecular genetics field, and allow researchers to investigate the interaction among the known environmental influences and various genotypes. Methods : In this study, we investigate factors contributing to variation in alcohol consumption of 156 rhesus macaques collected over 10 years when subjects were adolescent in age, belonging to a single extended pedigree, with each cohort receiving identical early rearing backgrounds and subsequent treatments. To measure alcohol consumption each animal was provided unfettered simultaneous access both to an aspartame-sweetened 8.4% (v/v) alcohol-water solution, the aspartame-sweetened vehicle, and to water for 1 hour each day during the early afternoon between 13:00 and 15:00 in their home cages for a period of 5 to 7 weeks. We use multiple regression to identify factors that significantly affect alcohol consumption among these animals and a maximum likelihood program (ASReml) that, controlling for the significant factors, estimates the genetic contribution to the variance in alcohol consumption. Results : Multiple regression analysis identified test cohort and rearing environment as contributing to 57 and 2%, respectively, of the total variance in alcohol consumption. Of the remaining 41% of the variance about half (19.8%) was attributable to additive genetic effects using a maximum likelihood program. Conclusion : This study demonstrates that, as in humans, there are additive genetic factors that contribute to variation in alcohol consumption in rhesus macaques, with other nongenetic factors accounting for substantial portions of the variance in alcohol consumption, Our findings show the presence of an additive genetic component and suggest the potential utility of the nonhuman primate as a molecular genetics tool for understanding alcohol abuse and alcoholism.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66182/1/j.1530-0277.2006.00044.x.pd

Effects of interspecific gene flow on the phenotypic variance–covariance matrix in Lake Victoria Cichlids

Quantitative genetics theory predicts adaptive evolution to be constrained along evolutionary lines of least resistance. In theory, hybridization and subsequent interspecific gene flow may, however, rapidly change the evolutionary constraints of a population and eventually change its evolutionary potential, but empirical evidence is still scarce. Using closely related species pairs of Lake Victoria cichlids sampled from four different islands with different levels of interspecific gene flow, we tested for potential effects of introgressive hybridization on phenotypic evolution in wild populations. We found that these effects differed among our study species. Constraints measured as the eccentricity of phenotypic variance–covariance matrices declined significantly with increasing gene flow in the less abundant species for matrices that have a diverged line of least resistance. In contrast, we find no such decline for the more abundant species. Overall our results suggest that hybridization can change the underlying phenotypic variance–covariance matrix, potentially increasing the adaptive potential of such populations

Epidemiology and heritability of Major Depressive Disorder, stratified by age of onset, sex, and illness course in Generation Scotland:Scottish Family Health Study (GS:SFHS)

The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found an intriguing difference in heritability between recurrent and single MDD illness course. These findings establish GS:SFHS as a valuable cohort for the genetic investigation of MDD

Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates

PURPOSE: Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics. METHODS: Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32+1 weeks (24+2-36+4) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35+2 weeks (25+3-43+1). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development. RESULTS: PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.). CONCLUSION: We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone

Prediction and estimation of effective population size

Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics, and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci, and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating Ne for future research

A fractal dimension for measures via persistent homology

We use persistent homology in order to define a family of fractal dimensions, denoted $\mathrm{dim}_{\mathrm{PH}}^i(\mu)$ for each homological dimension $i\ge 0$, assigned to a probability measure $\mu$ on a metric space. The case of $0$-dimensional homology ($i=0$) relates to work by Michael J Steele (1988) studying the total length of a minimal spanning tree on a random sampling of points. Indeed, if $\mu$ is supported on a compact subset of Euclidean space $\mathbb{R}^m$ for $m\ge2$, then Steele's work implies that $\mathrm{dim}_{\mathrm{PH}}^0(\mu)=m$ if the absolutely continuous part of $\mu$ has positive mass, and otherwise $\mathrm{dim}_{\mathrm{PH}}^0(\mu)<m$. Experiments suggest that similar results may be true for higher-dimensional homology $0<i<m$, though this is an open question. Our fractal dimension is defined by considering a limit, as the number of points $n$ goes to infinity, of the total sum of the $i$-dimensional persistent homology interval lengths for $n$ random points selected from $\mu$ in an i.i.d. fashion. To some measures $\mu,$ we are able to assign a finer invariant, a curve measuring the limiting distribution of persistent homology interval lengths as the number of points goes to infinity. We prove this limiting curve exists in the case of $0$-dimensional homology when $\mu$ is the uniform distribution over the unit interval, and conjecture that it exists when $\mu$ is the rescaled probability measure for a compact set in Euclidean space with positive Lebesgue measure

Appropriate model use for predicting elevations and inundation extent for extreme flood events

Flood risk assessment is generally studied using flood simulation models; however, flood risk managers often simplify the computational process; this is called a “simplification strategy”. This study investigates the appropriateness of the “simplification strategy” when used as a flood risk assessment tool for areas prone to flash flooding. The 2004 Boscastle, UK, flash flood was selected as a case study. Three different model structures were considered in this study, including: (1) a shock-capturing model, (2) a regular ADI-type flood model and (3) a diffusion wave model, i.e. a zero-inertia approach. The key findings from this paper strongly suggest that applying the “simplification strategy” is only appropriate for flood simulations with a mild slope and over relatively smooth terrains, whereas in areas susceptible to flash flooding (i.e. steep catchments), following this strategy can lead to significantly erroneous predictions of the main parameters—particularly the peak water levels and the inundation extent. For flood risk assessment of urban areas, where the emergence of flash flooding is possible, it is shown to be necessary to incorporate shock-capturing algorithms in the solution procedure, since these algorithms prevent the formation of spurious oscillations and provide a more realistic simulation of the flood levels

Genetic variation of male reproductive success in a laboratory population of Anopheles gambiae

<p>Abstract</p> <p>Background</p> <p>For Anopheline mosquitoes, the vectors of human malaria, genetic variation in male reproductive success can have important consequences for any control strategy based on the release of transgenic or sterile males.</p> <p>Methods</p> <p>A quantitative genetics approach was used to test whether there was a genetic component to variation in male reproductive success in a laboratory population of <it>Anopheles gambiae</it>. Swarms of full sibling brothers were mated with a fixed number of females and their reproductive success was measured as (1) proportion of ovipositing females, (2) proportion of ovipositing females that produced larvae, (3) proportion of females that produced larvae, (4) number of eggs laid per female, (5) number of larvae per ovipositing female and (6) number of larvae per female.</p> <p>Results</p> <p>The proportion of ovipositing females (trait 1) and the proportion of ovipositing females that produced larvae (trait 2) differed among full sib families, suggesting a genetic basis of mating success. In contrast, the other measures of male reproductive success showed little variation due to the full sib families, as their variation are probably mostly due to differences among females. While age at emergence and wing length of the males were also heritable, they were not associated with reproductive success. Larger females produced more eggs, but males did not prefer such partners.</p> <p>Conclusion</p> <p>The first study to quantify genetic variation for male reproductive success in <it>A. gambiae </it>found that while the initial stages of male reproduction (i.e. the proportion of ovipositing females and the proportion of ovipositing females that produced larvae) had a genetic basis, the overall reproductive success (i.e. the mean number of larvae per female) did not.</p