A comparison of three methods of Mendelian randomization when the genetic instrument, the risk factor and the outcome are all binary.

The method of instrumental variable (referred to as Mendelian randomization when the instrument is a genetic variant) has been initially developed to infer on a causal effect of a risk factor on some outcome of interest in a linear model. Adapting this method to nonlinear models, however, is known to be problematic. In this paper, we consider the simple case when the genetic instrument, the risk factor, and the outcome are all binary. We compare via simulations the usual two-stages estimate of a causal odds-ratio and its adjusted version with a recently proposed estimate in the context of a clinical trial with noncompliance. In contrast to the former two, we confirm that the latter is (under some conditions) a valid estimate of a causal odds-ratio defined in the subpopulation of compliers, and we propose its use in the context of Mendelian randomization. By analogy with a clinical trial with noncompliance, compliers are those individuals for whom the presence/absence of the risk factor X is determined by the presence/absence of the genetic variant Z (i.e., for whom we would observe X = Z whatever the alleles randomly received at conception). We also recall and illustrate the huge variability of instrumental variable estimates when the instrument is weak (i.e., with a low percentage of compliers, as is typically the case with genetic instruments for which this proportion is frequently smaller than 10%) where the inter-quartile range of our simulated estimates was up to 18 times higher compared to a conventional (e.g., intention-to-treat) approach. We thus conclude that the need to find stronger instruments is probably as important as the need to develop a methodology allowing to consistently estimate a causal odds-ratio.

Variations on the nutritional status of eucalypt as influenced by the genetic material and age of tree

The Diagnosis and Recommendation System (DRIS) was applied to eucalypt trees (hybrids of Eucalyptus grandis x E. urophylla) with different ages and growing under different environmental conditions for three different clones. The basic data were obtained from 1,986 trees of commercial stands cultivated in the states of Espírito Santo and south Bahia, Brazil. The DRIS indices were calculated using the Beaufils' Range formula and grouped according to the Nutrient Application Potential Response method. The objective of this paper was to evaluate the N, P and Ca status in eucalypt trees, regarding the tree ages and genetic materials. The DRIS indices discriminated differences in the nutritional status of the trees, both in relation to age and the genetic materials (clones). The results indicated that the deficiency of N and Ca tended to decrease with tree age, whereas the P deficiency tended to increase. Furthermore, of the three evaluated clones, those numbered 00014 and 00034 showed opposite trends regarding to N, P, and Ca nutrition, and the clone numbered 00021, in general, presented the highest degree of unbalanced nutrition of N, P and Ca.

Dissecting the genetic heterogeneity of depression through age at onset.

Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder. © 2012 Wiley Periodicals, Inc.

Optimization of particle bombardment parameters for the genetic transformation of Brazilian maize inbred lines

The objective of this work was to develop a genetic transformation system for tropical maize genotypes via particle bombardment of immature zygotic embryos. Particle bombardment was carried out using a genetic construct with bar and uidA genes under control of CaMV35S promoter. The best conditions to transform maize tropical inbred lines L3 and L1345 were obtained when immature embryos were cultivated, prior to the bombardment, in higher osmolarity during 4 hours and bombarded at an acceleration helium gas pressure of 1,100 psi, two shots per plate, and a microcarrier flying distance of 6.6 cm. Transformation frequencies obtained using these conditions ranged from 0.9 to 2.31%. Integration of foreign genes into the genome of maize plants was confirmed by Southern blot analysis as well as bar and uidA gene expressions. The maize genetic transformation protocol developed in this work will possibly improve the efficiency to produce new transgenic tropical maize lines expressing desirable agronomic characteristics.

Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics

A workshop recently held at the Ecole Polytechnique Federale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

Interference of genotypes x environments interaction in the genetic control of resistance to Asian rust soybean

The objectives of this work were to identify parents resistant to Asian soybean rust using diallel crosses, obtain information on the genetic control of soybean resistance to the pathogen and verify whether the combining ability estimates interact with the environment (year or time of assessment). The F1 generation was obtained in a greenhouse from crosses between five contrasting parents for the trait resistance to soybean rust, in a complete diallel without reciprocals. Two rust-severity assessments were carried out on individual soybean plants of 25 treatments (parents and F2 and F3 populations) in 2006/2007 and 2007/2008, in an experimental field at Embrapa Soja, Londrina, PR, Brazil. Additive effects predominated in the genetic control of soybean resistance to Asian rust, and the interaction of the segregant populations with the environment, although significant, did not alter the genetic parameter's general combining ability (GCA) and specific combining ability estimates, indicating that estimates obtained in one year and one assessment can be extrapolated to others. BR01-18437 inbred line is resistant to Asian rust and showed high GCA effects. This line should be used as parent if the objective is the resistance to Phakopsora pachyrhizi.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

How a haemosporidian parasite of bats gets around: the genetic structure of a parasite, vector and host compared.

Parasite population structure is often thought to be largely shaped by that of its host. In the case of a parasite with a complex life cycle, two host species, each with their own patterns of demography and migration, spread the parasite. However, the population structure of the parasite is predicted to resemble only that of the most vagile host species. In this study, we tested this prediction in the context of a vector-transmitted parasite. We sampled the haemosporidian parasite Polychromophilus melanipherus across its European range, together with its bat fly vector Nycteribia schmidlii and its host, the bent-winged bat Miniopterus schreibersii. Based on microsatellite analyses, the wingless vector, and not the bat host, was identified as the least structured population and should therefore be considered the most vagile host. Genetic distance matrices were compared for all three species based on a mitochondrial DNA fragment. Both host and vector populations followed an isolation-by-distance pattern across the Mediterranean, but not the parasite. Mantel tests found no correlation between the parasite and either the host or vector populations. We therefore found no support for our hypothesis; the parasite population structure matched neither vector nor host. Instead, we propose a model where the parasite's gene flow is represented by the added effects of host and vector dispersal patterns.

The interplay of spatial and climatic landscapes in the genetic distribution of a South American parrot

AimOur aim was to understand the interplay of heterogeneous climatic and spatial landscapes in shaping the distribution of nuclear microsatellite variation in burrowing parrots, Cyanoliseus patagonus. Given the marked phenotypic differences between populations of burrowing parrots we hypothesized an important role of geographical as well climatic heterogeneity in the population structure of this species. LocationSouthern South America. MethodsWe applied a landscape genetics approach to investigate the explicit patterns of genetic spatial autocorrelation based on both geography and climate using spatial principal component analysis (sPCA). This necessitated a novel statistical estimation of the species climatic landscape, considering temperature- and precipitation-based variables separately to evaluate their weight in shaping the distribution of genetic variation in our model system. ResultsGeographical and climatic heterogeneity successfully explained molecular variance in burrowing parrots. sPCA divided the species distribution into two main areas, Patagonia and the pre-Andes, which were connected by an area of geographical and climatic transition. Moreover, sPCA revealed cryptic and conservation-relevant genetic structure: the pre-Andean populations and the transition localities were each divided into two groups, each management units for conservation. Main conclusionssPCA, a method originally developed for spatial genetics, allowed us to unravel the genetic structure related to spatial and climatic landscapes and to visualize these patterns in landscape space. These novel climatic inferences underscore the importance of our modified sPCA approach in revealing how climatic variables can drive cryptic patterns of genetic structure, making the approach potentially useful in the study of any species distributed over a climatically heterogeneous landscape.

Analysis of the genetic basis of periodic fever with aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome.

PFAPA syndrome is the most common autoinflammatory syndrome in children from Western countries. In spite of its strong familial clustering, its genetic basis and inheritance pattern are still unknown. We performed a comprehensive genetic study on 68 individuals from 14 families. Linkage analysis suggested a susceptibility locus on chromosome 8, but direct molecular sequencing did not support this initial statistical finding. Exome sequencing revealed the absence of any gene that was mutated in all patients. Exhaustive screening of genes involved in other autoinflammatory syndromes or encoding components of the human inflammasome showed no DNA variants that could be linked to PFAPA molecular pathology. Among these, the previously-reported missense mutation V198M in the NLRP3 gene was clearly shown not to co-segregate with PFAPA. Our results on this relatively large cohort indicate that PFAPA syndrome is unlikely to be a monogenic condition. Moreover, none of the several genes known to be involved in inflammation or in autoinflammatory disorders seem to be relevant, alone, to its etiology, suggesting that PFAPA results from oligogenic or complex inheritance of variants in multiple disease genes and/or non-genetic factors.

The genetic content of chromosomal inversions across a wide latitudinal gradient

There is increasing evidence regarding the role of chromosomal inversions in relevant biological processes such as local adaptation and speciation. A classic example of the adaptive role of chromosomal polymorphisms is given by the clines of inversion frequencies in Drosophila subobscura, repeatable across continents. Nevertheless, not much is known about the molecular variation associated with these polymorphisms. We characterized the genetic content of ca. 600 individuals from nine European populations following a latitudinal gradient by analysing 19 microsatellite loci from two autosomes (J and U) and the sex chromosome (A), taking into account their chromosomal inversions. Our results clearly demonstrate the molecular genetic uniformity within a given chromosomal inversion across a large latitudinal gradient, particularly from Groningen (Netherlands) in the north to Málaga (Spain) in the south, experiencing highly diverse environmental conditions. This low genetic differentiation within the same gene arrangement across the nine European populations is consistent with the local adaptation hypothesis for th evolutionof chromosomal polymorphisms. We also show the effective role of chromosomal inversions in maintaining different genetic pools within these inverted genomic regions even in the presence of high gene flow. Inversions represent thus an important barrier to gene flux and can help maintain specific allelic combinations with positive effects on fitness. Consistent patterns of microsatellite allele-inversion linkage disequilibrium particularly in loci within inversions were also observed. Finally, we identified areas within inversions presenting clinal variation that might be under selection.

The genetic basis of color-related local adaptation in a ring-like colonization around the Mediterranean.

Uncovering the genetic basis of phenotypic variation and the population history under which it established is key to understand the trajectories along which local adaptation evolves. Here, we investigated the genetic basis and evolutionary history of a clinal plumage color polymorphism in European barn owls (Tyto alba). Our results suggest that barn owls colonized the Western Palearctic in a ring-like manner around the Mediterranean and meet in secondary contact in Greece. Rufous coloration appears to be linked to a recently evolved nonsynonymous-derived variant of the melanocortin 1 receptor (MC1R) gene, which according to quantitative genetic analyses evolved under local adaptation during or following the colonization of Central Europe. Admixture patterns and linkage disequilibrium between the neutral genetic background and color found exclusively within the secondary contact zone suggest limited introgression at secondary contact. These results from a system reminiscent of ring species provide a striking example of how local adaptation can evolve from derived genetic variation.