Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Population genetic structure and demography analysis in palinurus elephas populations from atlantic and mediterranean waters

Report for the scientific sojourn at the University of Reading, United Kingdom, from January until May 2008. The main objectives have been firstly to infer population structure and parameters in demographic models using a total of 13 microsatellite loci for genotyping approximately 30 individuals per population in 10 Palinurus elephas populations both from Mediterranean and Atlantic waters. Secondly, developing statistical methods to identify discrepant loci, possibly under selection and implement those methods using the R software environment. It is important to consider that the calculation of the probability distribution of the demographic and mutational parameters for a full genetic data set is numerically difficult for complex demographic history (Stephens 2003). The Approximate Bayesian Computation (ABC), based on summary statistics to infer posterior distributions of variable parameters without explicit likelihood calculations, can surmount this difficulty. This would allow to gather information on different demographic prior values (i.e. effective population sizes, migration rate, microsatellite mutation rate, mutational processes) and assay the sensitivity of inferences to demographic priors by assuming different priors.

Current genetic data do not improve the prediction of type 2 diabetes mellitus: the CoLaus study.

CONTEXT: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data. OBJECTIVE: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM. DESIGN: This was a prospective study, with a mean follow-up time of 5 yr. SETTING AND SUBJECTS: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr). MAIN OUTCOME MEASURE: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference. RESULTS: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement. CONCLUSIONS: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Population genetic structure of the major malaria vector Anopheles darlingi (Diptera: Culicidae) from the Brazilian Amazon, using microsatellite markers

The population genetic structure of Anopheles darlingi, the major human malaria vector in the Neotropics, was examined using seven microsatellite loci from nine localities in central and western Amazonian Brazil. High levels of genetic variability were detected (5-25 alleles per locus; H E = 0.519-0.949). There was deviation from Hardy-Weinberg Equilibrium for 59.79% of the tests due to heterozygote deficits, while the analysis of linkage disequilibrium was significant for only two of 189 (1.05%) tests, most likely caused by null alleles. Genetic differentiation (F ST = 0.001-0.095; Nm = 4.7-363.8) indicates that gene flow is extensive among locations < 152 km apart (with two exceptions) and reduced, but not absent, at a larger geographic scale. Genetic and geographic distances were significantly correlated (R² = 0.893, P < 0.0002), supporting the isolation by distance (IBD) model. The overall estimate of Ne was 202.4 individuals under the linkage disequilibrium model, and 8 under the heterozygote excess model. Analysis of molecular variance showed that nearly all variation (~ 94%) was within sample locations. The UPGMA phenogram clustered the samples geographically, with one branch including 5/6 of the state of Amazonas localities and the other branch the Acre, Rondônia, and remaining Amazonas localities. Taken together, these data suggest little genetic structure for An. darlingi from central and western Amazonian Brazil. These findings also imply that the IBD model explains nearly all of the differentiation detected. In practical terms, populations of An. darlingi at distances < 152 km should respond similarly to vector control measures, because of high gene flow.

Forecasting changes in population genetic structure of alpine plants in response to global warming.

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.

Low dispersing species : population genetic processes in space and time : the genus "Trochulus" (Gastropoda: Hygromiidae) as a case study

RÉSUMÉ Une espèce est rarement composée d'une population unique. Parce que les individus ont des capacités de dispersion limitées et que les paysages sont des mosaïques d'habitats, la plupart des espèces sont plutôt composées de sous-populations connectées par la migration. Cette variation spatiale influence directement la distribution de la variabilité génétique dans et entre les populations. Durant ce travail, nous avons abordé certains des processus populationnels qui ont joué un rôle supposé dans l'apparition de nouvelles espèces au sein du genre Trochulus. Plus précisément, nous avons tenté d'évaluer les impacts respectifs de l'isolement passé (facteurs historiques) et présent (facteurs locaux). Nous avons d'abord pu montrer que les faibles capacités de dispersion des escargots terrestres ont directement influencé leur histoire évolutive à toutes les échelles spatiales et temporelles. En réduisant l'effet homogénéisant de la migration, une faible dispersion maintient dans les populations les traces génétiques d'évènements passés. A l'échelle de la distribution globale de Trochulus villosus, ces traces ont permis de reconstruire une histoire faite d'isolements et d'expansions de populations. En combinant des données génétiques avec une modélisation de la niche climatique passée, il a été possible de proposer un scénario significativement meilleur que toutes les hypothèses alternatives que nous avons testées. A l'échelle locale par contre, l'héritage historique est difficile à distinguer de la dynamique actuelle. Ce fut le cas des lignées mitochondriales du complexe sericeus-hispidus : les deux principales lignées étaient phylogénétiquement éloignées, avaient eu des démographies passées différentes et corrélaient avec des différences morphologiques. D'un autre côté, le flux de gène nucléaire était fort, contredisant l'idée de deux espèces cryptiques isolées reproductivement. Pour pouvoir conclure à la présence ou non de deux espèces, il nous a manqué des informations locales sur la dynamique des populations et les conditions écologiques que l'on trouve dans la région d'étude. Enfin, nous avons pu souligner que la connectivité entre populations d'escargots est soumise à la qualité des habitats et à leur organisation spatiale. Les escargots sont dépendants d'un habitat et s'y adaptent, comme l'indiquent la présence de «poils » uniquement sur la coquille d'espèces vivant dans des habitats humides ou la corrélation entre morphologie et habitat au sein du complexe sericeus-hispidus. Logiquement donc, les escargots migrent préférentiellement au travers d'habitats favorables comme l'a montré la réduction de flux de gènes au travers des prairies chez T. villosus (une espèce forestière). De ces données, nous pouvons supposer que les populations d'escargots en particulier, et des espèces à faible dispersion en général, ont de fortes chances d'être affectées par les changements climatiques, avec de probables implications pour leurs histoires évolutives. SUMMARY : Species rarely consists in a single population. Because individuals have limited dispersal abilities, because landscapes are habitat patchworks, most species are made of several subpopulations connected by migration. This spatial variation has consequences on the distribution of genetic diversity within and between populations, creating a structure among the populations. During the present work, we investigated some of the population processes assumed to have played an important role on the speciation within the genus Trochulus. More specifically, we questioned the respective impacts of past (historical factors) or present (local factors) population isolations. We first could show that the poor dispersal abilities of land snails have had profound impacts on their evolutionary histories at all spatial and temporal scales. Low dispersal maintains a strong signature of past events in the populations by minimising the homogenising effects of geneflow. At the scale of Trochulus villosus global distribution, they allowed to retrieve the detailed history of this species population isolations and expansions. Combining a large genetic dataset with paleo-climatic niche modelling ended up with a historical scenario significantly better than all traditional alternatives we tested. At local scale on the contrary, past events become difficult to tease apart from ongoing processes. This was the case for the divergent mitochondria) lineages within the sericeus-hispidus complex: the two principal lineages appeared to be phylogenetically distant, to have experienced different demographic histories and to correlate with morphological differences. On the other hand, nuclear (present day) geneflow was high, contradicting the idea of two reproductively isolated cryptic species. Information on the local population dynamics and environmental conditions are lacking to be able to decide whether past isolation has indeed resulted here in new species. Finally, we emphasised the importance of the habitat types present in a landscape as well as their spatial organisation for the population connectivity of land snails. These species are tightly dependent on a habitat and adapt to it as shown by thé occurrence of hair-like structures only in species living in humid environments or by the correlation between shell morphology and habitat in the sericeus-hispidus complex. As a result, land snails preferentially migrate through favourable habitats: Trochulus villosus, a forest species, had its geneflow significantly reduced across meadows. From these data, we can hypothesise that the populations of land snails in particular and of low dispersing species in general are likely to be strongly affected by the ongoing climate changes, with potential major consequences on their evolutionary histories.

Population pharmacokinetic study of memantine: effects of clinical and genetic factors.

BACKGROUND AND OBJECTIVE: Memantine, a frequently prescribed anti-dementia drug, is mainly eliminated unchanged by the kidneys, partly via tubular secretion. Considerable inter-individual variability in plasma concentrations has been reported. We aimed to investigate clinical and genetic factors influencing memantine disposition. METHODS: A population pharmacokinetic study was performed including data from 108 patients recruited in a naturalistic setting. Patients were genotyped for common polymorphisms in renal cation transporters (SLC22A1/2/5, SLC47A1, ABCB1) and nuclear receptors (NR1I2, NR1I3, RXR, PPAR) involved in transporter expression. RESULTS: The average clearance was 5.2 L/h with a 27 % inter-individual variability (percentage coefficient of variation). Glomerular filtration rate (p = 0.007) and sex (p = 0.001) markedly influenced memantine clearance. NR1I2 rs1523130 was identified as the unique significant genetic covariate for memantine clearance (p = 0.006), with carriers of the NR1I2 rs1523130 CT/TT genotypes presenting a 16 % slower memantine elimination than carriers of the CC genotype. CONCLUSION: The better understanding of inter-individual variability of memantine disposition might be beneficial in the context of individual dose optimization.

Genetic Differentiation of the Cabo Verde Archipelago Population Analysed by STR Polymorphisms

Allele frequencies for 17 STR loci were analyzed in a sample of unrelated males from the Cabo Verde Archipelago. The samples were gathered in such a way that the origin of the subjects was perfectly identified, and they could be included in one of the leeward or windward groups of islands. This study reveals that there are significant differences between both groups of islands, and between Cabo Verdeans and other populations from sub-Sahara Africa including the Guineans, the most probable source population for Cabo Verdeans. This study confirms mtDNA data and, together with HLA and Y chromosome data already published, shows that the Cabo Verde population is substructured and atypical, diverging substantially from mainland sub-Saharan populations. Overall these differences are most probably due to admixture between sub-Saharan slaves brought into the islands and other settlers of European origin. In the absence of a clear indication of a different ethnic composition of the first sub-Saharan settlers of Cabo Verde, the differentiation exhibited in both groups of islands can be most probably be attributed to genetic drift.

Genetic association tests: a method for the joint analysis of family and case-control data.

With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.

Spatio-temporal population genetic structure of the parasitic mite Spinturnix bechsteini is shaped by its own demography and the social system of its bat host.

Information about the population genetic structures of parasites is important for an understanding of parasite transmission pathways and ultimately the co-evolution with their hosts. If parasites cannot disperse independently of their hosts, a parasite's population structure will depend upon the host's spatial distribution. Geographical barriers affecting host dispersal can therefore lead to structured parasite populations. However, how the host's social system affects the genetic structure of parasite populations is largely unknown. We used mitochondrial DNA (mtDNA) to describe the spatio-temporal population structure of a contact-transmitted parasitic wing mite (Spinturnix bechsteini) and compared it to that of its social host, the Bechstein's bat (Myotis bechsteinii). We observed no genetic differentiation between mites living on different bats within a colony. This suggests that mites can move freely among bats of the same colony. As expected in case of restricted inter-colony dispersal, we observed a strong genetic differentiation of mites among demographically isolated bat colonies. In contrast, we found a strong genetic turnover between years when we investigated the temporal variation of mite haplotypes within colonies. This can be explained with mite dispersal occuring between colonies and bottlenecks of mite populations within colonies. The observed absence of isolation by distance could be the result from genetic drift and/or from mites dispersing even between remote bat colonies, whose members may meet at mating sites in autumn or in hibernacula in winter. Our data show that the population structure of this parasitic wing mite is influenced by its own demography and the peculiar social system of its bat host.

Genetic bottlenecks driven by population disconnection.

Connectivity among populations plays a crucial role in maintaining genetic variation at a local scale, especially in small populations affected strongly by genetic drift. The negative consequences of population disconnection on allelic richness and gene diversity (heterozygosity) are well recognized and empirically established. It is not well recognized, however, that a sudden drop in local effective population size induced by such disconnection produces a temporary disequilibrium in allelic frequency distributions that is akin to the genetic signature of a demographic bottleneck. To document this effect, we used individual-based simulations and empirical data on allelic richness and gene diversity in six pairs of isolated versus well-connected (core) populations of European tree frogs. In our simulations, population disconnection depressed allelic richness more than heterozygosity and thus resulted in a temporary excess in gene diversity relative to mutation drift equilibrium (i.e., signature of a genetic bottleneck). We observed a similar excess in gene diversity in isolated populations of tree frogs. Our results show that population disconnection can create a genetic bottleneck in the absence of demographic collapse.

Decades of population genetic research reveal the need for harmonization of molecular markers: the grey wolf Canis lupus as a case study

Following protection measures implemented since the 1970s, large carnivores are currently increasing in number and returning to areas from which they were absent for decades or even centuries. Monitoring programmes for these species rely extensively on non-invasive sampling and genotyping. However, attempts to connect results of such studies at larger spatial or temporal scales often suffer from the incompatibility of genetic markers implemented by researchers in different laboratories. This is particularly critical for long-distance dispersers, revealing the need for harmonized monitoring schemes that would enable the understanding of gene flow and dispersal dynamics. Based on a review of genetic studies on grey wolves Canis lupus from Europe, we provide an overview of the genetic markers currently in use, and identify opportunities and hurdles for studies based on continent-scale datasets. Our results highlight an urgent need for harmonization of methods to enable transnational research based on data that have already been collected, and to allow these data to be linked to material collected in the future. We suggest timely standardization of newly developed genotyping approaches, and propose that action is directed towards the establishment of shared single nucleotide polymorphism panels, next-generation sequencing of microsatellites, a common reference sample collection and an online database for data exchange. Enhanced cooperation among genetic researchers dealing with large carnivores in consortia would facilitate streamlining of methods, their faster and wider adoption, and production of results at the large spatial scales that ultimately matter for the conservation of these charismatic species.